phd computer science texas

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Doctor of Philosophy - Computer Science

Advisory committee.

The Ph.D. advisory committee is the same as the Master of Science in Computer Science degree except that it must have a minimum of four members, a majority from the department and at least one from another department.  This is a STEM program.

Degree Plan

The degree plan should be completed by the student in consultation with the chair and the advisory committee. Requirements for the Ph.D. in computer science degree include:

• At least 30 credit hours of graded graduate coursework (excluding 681, 684, 685 and 691).
• Three breadth CSCE courses, one selected from each of these sets: Theory (627, 629), Systems (605, 611, 613, 614 and 678) and Software (604, 606, 634, 655, 656, 670, 671, 672 and 713). These must be passed with a grade of B or better. These count toward the requirement of 30 hours of graded graduate coursework.
• At most, six credit hours of approved non-CSCE graded graduate coursework (excluding 681, 684, 685, 691). This counts towards the requirement of 30 hours of graded graduate coursework.
• One to two credit hours of CSCE 681 (Graduate Seminar).
• At least 18 credit hours of CSCE 691 (Research). Normally, the number of CSCE 691 hours will be increased to meet the required total number of credit hours.
• A total of at least 96 credit hours (or at least 64 credit hours if the student has a prior approved and related master’s degree).

Courses That Cannot Be Used on Any Degree Plan:

• In CSCE, we do not allow 601, 602, 603, 701, 705, 706, 707, 708, 709.
• In ECEN, we do not allow 714, 749.
• In STAT, we do not allow 624 and 654.
• In MATH, we do not allow 679.
• In CYBR, we do not allow 601.
• Any course that contains material required of our undergraduate computer science or computer engineering majors.

Other Degree Plan Information:

• Texas A&M undergraduates who have taken 410 cannot use 611 on their degree plan. If the Texas A&M undergraduate receives an A in 410, they satisfy the Systems breadth requirement for the CPSC degrees.
• Texas A&M undergraduates who have taken 431 cannot use 606 on their degree plan. Texas A&M undergraduates who receive an A in 431 satisfy the Software breadth requirement for the CPSC degrees.
• Texas A&M undergraduates who have taken 420 cannot use 625 on their degree plan. This course is not stacked normally but overlaps by about two-thirds (2/3).
• Texas A&M undergraduates who receive an A in 411 satisfy the Theory breadth requirement.
• 401/701 (always)
• 402/702 (always)
• 403/703 (always)
• 410/611 (sometimes)
• 413/713 (always)
• 421/633 (always)
• 433/627 (always)
• 435/735 (sometimes) 
• 440/640 (sometimes)
• 445/656 (always)
• 447/679 (always)
• 451/652 (always)
• 452/752 (always)
• 463/612 (always)
• 465/765 (sometimes)
• 469/614 (always)
• 477/703 (always)
• Texas A&M undergraduates can receive credit for both courses in an undergrad/grad course pair under Fast Track.
• Prerequisites listed for CSE graduate coursework are given to inform students of the knowledge they are expected to have to be successful in the graduate course. While the department does not block registration based on prerequisites for graduate courses, students are still responsible for ensuring they are prepared to meet course prerequisites. If students have concerns regarding preparation for a particular class, they should contact the instructor of the graduate course for more information regarding expectations.

CSCE 684 Hours:

• Any international student who wishes to go on to do curricular practical training must have one credit hour for each semester they are on the internship of CSCE 684 on their degree plan. Any CSCE 684 hours are in addition to the required total credit hours of the degree plan.
• If you are an international student, we recommend you place at least one credit hour of CSCE 684 on your degree plan when you submit it. This way if you receive an internship offer, you will not be rushing to have 684 added to your degree plan.
• Domestic students do not need to register when they are on an internship. However, if they are gone for a year without registering, they must apply for a leave of absence. Otherwise, they will need to reapply for admission.

For additional information and clarification, please see the graduate catalog and the department’s graduate program webpage .

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Doctor of Philosophy in Computer Science

Program description.

The graduate programs in computer science offer intensive preparation in design, programming, theory and applications. Training is provided for both academically oriented students and students with professional goals in the many business, industrial and governmental occupations requiring advanced knowledge of computing theory and technology.

Courses and research opportunities are offered in a variety of subfields of computer science, including operating systems, computer architecture, computer graphics, pattern recognition, automata theory, combinatorics, artificial intelligence, machine learning, database design, computer networks, programming languages, software systems, analysis of algorithms, computational complexity, parallel processing, VLSI, virtual reality, internet of things, embedded and real-time systems, computational geometry, computer vision, design automation, cyber security, information assurance and data science.

The University maintains a large network of computer facilities including specialized computers for research within the program. In addition to computer science faculty, many other individuals at the University are involved in computer-related work in the physical and social sciences and in various areas of business and management. Computer science students with an interest in these important application areas may have opportunities to consult and work with talented faculty from a wide range of disciplines.

Career Opportunities

Graduates of the program seek academic positions at universities, as well as positions as researchers, senior software engineers, data scientists. Graduates often become industry experts in fields like cyber security, artificial intelligence, machine learning or natural language processing.

Marketable Skills

Review the marketable skills for this academic program.

Application Requirements

Test score required:  Yes

Deadlines:  University  deadlines  apply.

OTHER APPLICATION REQUIREMENTS

Admission Option One

• Master’s degree in computer science or its equivalent
• GPA of at least 3.5
• GRE revised scores of at least 308, 153, 155 and 4 for the combined, verbal, quantitative, and analytical writing components, respectively, are advisable.

Admission Option Two

• A BS degree in related area that includes two semesters of calculus and linear algebra
• GPA of at least 3.5 in the last 60 semester credit hours
• GRE revised scores of at least 315, 156, 159 and 4 for the combined, verbal, quantitative, and analytical writing components, respectively, are advisable.

Applicants are admitted on a competitive basis.

Contact Information

Shyam Karrah  Email: [email protected]

Dr. Ovidiu Daescu Interim Head Department of Computer Science Email: [email protected] Office: ECSS 3.904

Erik Jonsson School of Engineering and Computer Science The University of Texas at Dallas, ECW41 800 W. Campbell Road Richardson, TX 75080-3021 [email protected]

engineering.utdallas.edu

cs.utdallas.edu

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• Department of Computer Science
• Ph.D. Degree

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Doctoral Degree Program

The Ph.D. degree program in Computer Science provides for a rigorous foundation in theoretical and applied computer science. Students obtain in-depth knowledge by satisfying a breadth course requirement intended to ensure broad knowledge of computer sciences as well as satisfy a depth requirement in the ability to conduct research to advance knowledge and application of Computer Sciences to diverse fields.

Our program places a strong emphasis on research and on graduates making novel contributions to Computer Science in the form of a dissertation and scholarly publications. Students pursuing the Ph.D. degree are trained to become teachers, researchers, and technical leaders in industry, academia, or research labs.

Students will be prepared to be technical problem solvers, competent in the state of the art, and will master a particular aspect of Computer Science. They will be trained to identify and clearly formulate problems, to develop and analyze algorithmic solutions, and to direct research.

The Ph.D. in Computer Science is a traditional face-to-face/in-person program. There is currently no option to complete it fully online.

Fall 2021 - present

Fall 2020 - summer 2021, fall 2017 - summer 2020, prior to fall 2017, course requirements.

Students who began the Ph.D. program Fall 2021 through present : A student must complete a minimum of 66 credit hours subject to the following restrictions:

• Can include 1 hour of COSC 6110
• Can include up to 3 hours of COSC 6398 Special Problems if taken within the first four longer terms of the program¹
• Can include up to 6 hours of non-COSC graduate courses¹
• Can include up to 9 hours of transfer graduate coursework following university   Transfer Credit policy ¹
• At least 24 credit hours of Doctoral Research (COSC 8x98).
• At least 3, but not more than 12 credit hours of dissertation (COSC 8x99), to be taken in the term of anticipated graduation.
• ¹Requires prior approval from the director of graduate studies via a Graduate & Professional Student Petition

Research Advisor

Students are urged to find a research advisor as early as possible. Full-time and part-time students must declare a research advisor by the end of the first long term by completing the Research Advisor Assignment form . Student may enroll in doctoral research hours once they have declared a research advisor.

Graduate Colloquium/Research Methods

All PhD students are required to pass COSC 6110 - Graduate Colloquium or COSC 6321 - Research Methods in Computer Science by the end of the second long term in the program.

Research Competency Evaluation (RCE) Exam

Spring 2024 RCE Exam date is Friday, April 19, 2024

PhD students are expected to spend a substantial amount of time on research starting in the first semester. The RCE requires students to learn and demonstrate specific skills necessary to doing research early in their career. These include the ability to perform a literature review, understand and synthesize research topics, conduct independent and collaborative research to the standards of the chosen discipline, and communicate the findings in a scholarly fashion.

For the RCE exam, the student (in consultation with their research advisor) selects and conducts research on a topic, writes an ACM/IEEE style paper, and presents a talk, to be approved by the student’s RCE committee. A student may submit and present their own submitted or published research for RCE requirements. The RCE committee will evaluate the student with respect to two questions:

• Has the student demonstrated scholarship and potential to conduct original research?
• Has the student demonstrated the ability to communicate technical content effectively to a general computer science audience?

RCE Process

The student’s research advisor, with the consultation of the student’s RCE committee, assigns a research topic to the student no later than the beginning of the third long term. The student may also receive an initial selection of relevant literature. The project should be designed to test the student’s ability to independently conduct research at a level commensurate with his/her education.

The student will prepare a written report and an oral presentation of the project results. The research advisor may provide feedback during the preparation of the written report, but the report should be substantially the student’s own work. The report should include a statement of the problem, present a critical survey of relevant methods and existing state of the art solutions to the problem, present their own methods and proposed solution, results, and discussion. The length of the report should be similar to a standard paper in the research area and be formatted using the IEEE or ACM docx or Latex templates. The report should be submitted to the student’s RCE committee at least one week prior to the RCE exam. The RCE exam consists of a public presentation of the project, followed by a closed–door oral examination.

RCE Committee

The student’s RCE committee should comprise of at least 3 Computer Science faculty members (not including the research advisor) and approved by the Director of Graduate Studies. At least one committee member should be from outside the student's research area. The research project topic for the RCE will be selected in consultation with the student’s research advisor. Once the evaluation has taken place, the Chair of the RCE committee will inform the student and the Director of Graduate Studies about the outcome of the exam. Should a student switch their research advisor after completing the RCE requirement, the student is not required to retake the RCE exam.

RCE Deadlines

The RCE exam must be completed by the end of the third long term of the PhD program. It is not necessary to complete all coursework before attempting the RCE exam. The RCE Exam is offered once each long term. Unless otherwise announced, in Fall it is offered the second or third Friday in November and in Spring it is offered the second or third Friday of April. The exact date RCE date for each semester will be announced at the beginning of the respective semester.

RCE Outcome

The student will either pass or fail the RCE exam, and this decision, based on a majority vote of the committee, will be communicated within one (1) week following the exam. Once the student passes, they may proceed with the preparation of the dissertation proposal. If failed, the student may request a second attempt. For a second attempt, the RCE committee will assign additional work, which should be completed and presented at the end of the next long term. Students who fail the second attempt will be discontinued from the PhD program.

Breadth Requirements

A student satisfies the core requirement by taking a set of three or more courses from the lists below. At least one course must be from the Theory list and one from the Systems list. The remaining course may be from either list. In exceptional cases, the Director of Graduate Studies may transfer or substitute at most two of the three courses based on equivalent courses taken at another university following transfer or course substitution policies. Similarly, any breadth course taken as a MS Computer Science student at UH may count towards the breadth requirement following transfer and course substitution policies. Time limitations apply to transferred and substituted courses.

Breadth Requirements Completion Period

The “breadth requirement completion period” begins as soon as the student has successfully passed the RCE Exam. The breadth requirement completion period applies to PhD students as well as MS students who later pursue the PhD program.

Full-time students must complete the breadth requirements in at most two consecutive long terms after passing the RCE Exam. Part-time students (6 hours or less every term) must complete the breadth requirement in at most four consecutive long terms after passing the RCE Exam. Failure to complete this requirement within the specified timeframe normally results in an MS student not being allowed to continue into the PhD program and a PhD student being dismissed from the PhD program.

Students who began the Ph.D. program Fall 2020 through Summer 2021 : A student must complete a minimum of 66 credit hours subject to the following restrictions:

• Can include up to 3 hours of COSC 6398 Special Problems¹

Graduate Colloquium/Research Method Courses

All Ph.D. students are required to take either the Graduate Colloquium course (COSC 6110) or the Research Method course (COSC 6321) within the first two years of enrollment.

Students are urged to find a research advisor as early as possible. Full-time and part-time students must have a research advisor declared by the end of the second long term by completing the Research Advisor Assignment form . Student may enroll in doctoral research hours if they have an advisor and have completed the core requirement.

Core Completion Period

The “core completion period” begins as soon as the student has accumulated 18 or more hours of credits applicable to a graduate degree (M.S. or Ph.D.) in Computer Science. These include transferred credits, waived credits, and credits earned at UH. The core completion period applies to Ph.D. students as well as M.S. students who later pursue the Ph.D. program. Full-time students must complete the core requirements in at most 2 consecutive long terms after the start of the core completion period. Part-time students (6 hours or less every term) must complete the core requirement in at most 4 consecutive long terms after the start of the core completion period. Failure to complete the core requirements with the required GPA and within the specified timeframe normally results in an M.S. student not being allowed to continue into the Ph.D. program and a Ph.D.  student being dismissed from the Ph.D. program.

Core Requirements

A student satisfies the core requirement by taking at least 4 core courses with:

• At least 2 courses from the Theory list
• At least 2 courses from the Systems list
• At least 3.40 or higher core course GPA
• No grade less than B

The Director of Graduate Studies may in exceptional cases waive at most 2 of the 4 courses based on similar courses taken at another university. If a students takes Ph.D. core courses while enrolled as an M.S. student in the UH Department of Computer Science and is subsequently admitted to the UH Computer Science Ph.D. program, any Ph.D. core courses taken within 5 years prior to the date of the Ph.D. admissions can count towards meeting the Ph.D. core requirement.

Full-time students must complete the core requirements in at most 2 long semesters after core completion period begins. Part-time students (6 hours or less every semester) must complete the core requirement in at most 4 long semesters after the core completion begins. Failure to complete the core requirements with the required grades and GPA within the core completion period normally results in an M.S. student not being allowed to continue into the Ph.D. program and a Ph.D. student being removed from the Ph.D. program.

Students who began the Ph.D. program Fall 2017 through Summer 2020 : A student must complete a minimum of 66 credit hours subject to the following restrictions:

• At least 30 credit hours of approved, regular, or special topics (COSC xx97) courses. At most 6 of these 30 hours may be outside the Department with the approval of the student’s research advisor and the Director of Graduate Studies.

Students who began the Ph.D. program prior to Fall 2017 : A student must complete a minimum of 72 credit hours subject to the following restrictions:

• At least 36 credits of approved, regular, or special topics (xx97) courses. At most 6 of these hours may be outside the Department with the approval of the student’s research advisor and the Director of Graduate Studies.
• Between 24 and 30 credits of research hours (8x98) to fulfill the 72 hour degree requirement.
• At least 6 but not more than 12 credits of dissertation (8x99).

COSC Academic Policies

The following are required of all COSC PhD students regardless of when they started the program except when noted.

• Declare a research advisor (also known as dissertation committee chair)
• Satisfactory completion of COSC 6110 or COSC 6321
• *Satisfactory completion of the Research Competency Evaluation (RCE) Exam ( *applicable to those in Catalog 2021-2022 and onward ) 
• Satisfactory completion of the Core/Breadth Requirement
• Declare a dissertation committee
• Proposal Defense (preliminary examination): written proposal and satisfactory defense thereof.
• Dissertation Defense: written dissertation and satisfactory defense thereof.
• Satisfactory performance on Annual Reviews
• Publication of doctoral research. It is recommended to work towards one or more publications before the proposal defense and additional publications or submissions before the dissertation defense.
• Attend at least 5 department seminars per term.  Effective January 2018. In addition, all Ph.D. students, regardless of year, are expected to attend at least one (1) Computer Science Focus on Research presentation per academic year. Ph.D. students in the third year or after are expected to present their research during at least one (1) Computer Science Focus on Research presentation per academic year.
• Maintain satisfactory progress. Failure to meet degree, department, college, and university requirements and policies may be dismissed from the PhD program.

Dissertations Committee

The dissertation committee must be comprised of a minimum of four members to include three internal members (inclusive of the research advisor who serves as the dissertation committee chair or co-chair) who have their primary faculty appointment within the major department and one approved external member from outside the major department at UH, industry or other academic institution who is acceptable to the department and approved by the college. A faculty member with a joint appointment in the major department is considered as an external member unless he/she chairs the committee. In this case, an additional external member outside the major department is required. After these minimum requirements for committee members are satisfied, additional committee members may be approved, but at least 50% of the committee must be tenured/tenure-track faculty at the University of Houston. Research faculty, instructional faculty and emeritus faculty may serve on dissertation committees, but not chair the committees. However, a research professor may serve as a co-advisor with a tenured/tenure-track faculty. For the purpose of the committee composition, an emeritus faculty is considered as internal non-tenure-track faculty member.

Proposal Defense

A student must pass a proposal defense (also referred as the preliminary examination) administered by the student’s dissertation committee. The purpose of the proposal defense is to evaluate and give feedback on the proposed dissertation research of the student. Candidates should have one or more publications before the proposal defense and additional publications or submissions before the dissertation defense.

The student must prepare the dissertation proposal document using the NSM PhD dissertation template and present the proposal to the dissertation committee. The proposal document should include an overview of the proposed work, relevant related work, completed work, and a plan for the work to be completed in the dissertation. The presentation should cover the same topics in the proposal document, and include a listing of coursework completed, publications, and a proposed timeline for key activities to complete in the dissertation. The proposal document should be submitted to the dissertation committee at least two weeks before the proposal defense.

Proposal Defense Announcement

The proposal defense is open to the public and should be announced two weeks in advance. All may ask the student questions related to the proposal or the student’s preparation for doctoral-level research. The committee may have a closed session with the student at the end of the proposal defense. Details on how to announce the defense can be found on the Defense Guidelines page.

Proposal Defense Evaluation Outcome

The committee will submit the  Proposal Defense Evaluation Form to the Director of Graduate Studies summarizing the student’s performance of the proposal defense and assign an overall evaluation of satisfactory (pass) or unsatisfactory (fail). A student will be informed of the outcome and upon receiving a satisfactory evaluation the student becomes a Ph.D. candidate.

Proposal Defense Deadline

Full-time and part-time students must attempt the proposal defense no later than the end of the third long term after completing the core/breadth requirement. The proposal defense cannot be held before fulfilling the core/breadth requirement. The proposal defense must be completed at least one term before the dissertation defense.

Dissertation Defense

A PhD candidate will be required to present their dissertation in a public defense. The dissertation defense and the proposal defense may not be scheduled in the same term. The dissertation committee decides the acceptability of the dissertation. Candidates are expected to publish results of their dissertation research prior to the dissertation defense. Candidates should have one or more publications before the proposal defense and additional publications or submissions before the dissertation defense.

Dissertation Defense Announcement

The dissertation defense is open to the University community and the student must inform the department at least two weeks in advance so that it can be publicized. Details on how to announce the defense can be found on the  Defense Guidelines  page.

Annual Review

Every PhD student must complete the formation of a dissertation committee no later than the end of the 2 nd  year in the program. Each student will be reviewed annually by the dissertation committee during a review meeting; the review is mandatory starting on the 3rd year. The review meeting should be integrated to the proposal defense in the year in which the proposal defense takes place, and it is not necessary in the year of the dissertation defense.

After meeting with the student, the dissertation committee will submit a “PhD Annual Review - Committee Evaluation Form” to the Director of Graduate Studies. The evaluation can be satisfactory “S”, unsatisfactory “U”, or needs improvement “NI”. If the student receives a “U” or “NI” grade, the student must be provided with a clear plan to return to a satisfactory status and reviewed again in the next long term. A subsequent evaluation of “NI” or “U” can result in removal of the program.

PhD Annual Review Deadlines

• Self-Evaluation Form must be submitted by the student before the following deadlines: October 31 (during fall reviews) or May 31 (during spring reviews)
• Committee Evaluation Form must be submitted by the dissertation committee no later than the end of the Spring or Fall semester.

Time Limitations

Students who enroll as doctoral candidates must complete their degree requirements within 10 years of the date of first enrollment with a doctoral degree objective. All courses used towards the degree, including transferred and substituted courses, must not be older than 10 years at the time of graduation. Failure to comply will result in the candidate being ineligible for a doctoral degree.

Doctoral students who fail to complete their dissertation within five years after completion of the comprehensive examination must retake the examination.

Refer to the  Time Limitations of Completion of Degree Requirements  section of the Graduate Catalog.

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Computer Science PhD Program

Doctoral Program

This PhD program provides cutting-edge research experience and expertise in advanced computer science subjects, aiming at educating future leaders in academia and industry.

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Why Pursue a Computer Science PhD

At UTSA, the Department of Computer Science offers comprehensive programs at both undergraduate and graduate levels, with approximately 1,761 undergraduates, 135+ master’s students and 65+ doctoral students. The PhD in Computer Science offers opportunities for students to do advanced research in many fields. The research activities and experimental facilities have been well-supported by various federal research and infrastructure grants.

Research Opportunities

The research in the Department of Computer Science is supported by more than $10M in active research grants and contracts from various external funding agencies. PhD students conduct innovative research in cooperation with and under the supervision of department faculty. Activities of research assistants include implementing prototype systems, developing and proving new theories, conducting experiments, attending international conferences, and publishing their results in scientific journals.

The department’s 21 faculty members conduct research in a variety of areas including algorithms, bioinformatics, computer and information security, computer architecture, computer networks, databases, high performance computing, parallel and distributed systems, programming languages and compilers, and software engineering among others.

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Application Deadlines

Funding opportunities, career options, admission & application requirements.

Applications are submitted through the UTSA Graduate Application . Please upload all required documents (listed below) on your UTSA Graduate Application. It is the applicant’s responsibility to ensure completion and submission of the application, a nonrefundable application fee, and all required supporting documents are on file with UTSA by the appropriate application deadline.

Applicants are encouraged to have their admission file completed as early as possible. All applications, required documents and letters of recommendation, if applicable, must be submitted by 5:00 PM U.S. Central Time on the day of the deadline. Deadlines are subject to change.

All full-time, admitted PhD students are welcomed with an appointment as either a Graduate Teaching Assistant (GTA) or Graduate Research Assistant (GRA). This is comprehensive support that comes with a tuition waiver, stipend, and health insurance. The stipend starts from $24,000 per year, and the total value of the financial support package is more than $42,000 yearly. The Computer Science PhD program is designed so that students who are admitted as GTAs find a doctoral advisor during their first year of study.

UTSA prepares you for future careers that are in demand. The possible careers below is data pulled by a third-party tool called Emsi, which pulls information from sources like the U.S. Bureau of Labor Statistics, U.S. Census Bureau, online job postings, other government databases and more to give you regional and national career outlook related to this academic program.

Earning a Master's Degree

While in a doctoral program, a student may earn a master’s degree provided the following conditions are satisfied:

• A student must be admitted to candidacy.
• A student is eligible to receive a master’s degree upon completion of University-wide requirements and any additional degree requirements specific to the program.
• The Doctoral Studies Committee, Department Chair, and the Graduate Associate Dean of the College must recommend students for the degree.
• The student must apply for graduation by the published deadline the semester prior to awarding the doctoral degree.
• All required coursework in the doctoral program at the time of admission to candidacy must have been taken within the previous six years.
• If the master’s degree requires a thesis, the degree cannot be awarded on the basis of the doctoral qualifying examination.
• Students will not be approved for an additional master’s degree in the same field in which an individual has previously received a master’s degree.

Course Offerings & Schedule

Faculty offices and research labs for Computer Science are located both on the Main Campus and Downtown Campus (San Pedro I building). Graduate courses are held in San Pedro I. Courses are scheduled in late afternoons and evenings, accommodating part-time student schedules very well.

Graduate Advisor of Record

Dakai Zhu, PhD

210-458-7453

College of Engineering

Computer Science, Ph.D.

This program emphasizes deep technical mastery of computer science through rigorous advanced coursework, as well as training in research methods in computer science. Students work closely with a faculty mentor in their area of interest and work in one of UTEP's acclaimed research centers such as the Army High Performance Computing Research Center or the Cyber-Share Center of Excellence.

Learn from world-class faculty well-versed in data mining, analytics design, machine learning and more.

Learn in state-of-the-art labs such as the Army High Performance Computing Research Center.

Collaborate with faculty and peers at leading U.S. institutions through the Computing Alliance of Hispanic-Serving Institutions.

GRAD RETURNS FOR PH.D. AND SUCCESS

Moinul Morshed Porag Chowdhury, Ph.D., worked for three years as a software engineer before deciding to pursue his doctoral degree. At UTEP, he honed his skills by developing cross-browser-tested web pages for a web content management system. He is now a research engineer with Indeed in Sugar Land, Texas.

Career Opportunities

This program offers courses in a variety of core and applied areas of CS that provides students with a strong foundation to build their individual research and professional programs. Our graduates find jobs at Microsoft, Google, Exxon and more.

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Computer Science and Engineering Ph.D.

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Why Earn a Computer Science and Engineering Ph.D.?

The program of study for the doctoral degree with a major in computer science and engineering includes formal course work, independent study and research. The purpose of the degree is to produce a professional capable of directing and conducting research within the discipline of computer science and engineering.

You'll be able to work closely with distinguished faculty members to solve complex problems faced by businesses and consumers.

Faculty research is supported through grants from federal and state institutions and private industry, including the:

• National Geospatial-Intelligence Agency
• National Institutes of Health
• National Science Foundation
• Texas Department of Transportation
• Texas State Energy Conservation Office
• U.S. Department of Education

The department offers comprehensive research that focuses on:

• Algorithms and Computational Science
• Computer Security
• Computer Systems and Networks
• Databases and Data Mining
• Intelligent Systems
• Complex problem-solving
• Advanced critical thinking
• Ability to conduct research
• Software development
• Advanced oral and written communication

Computer Science and Engineering Ph.D. Highlights

Computer science and engineering ph.d. courses you could take.

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Computer Science (Ph.D.)

Ph.d. computer science (doctoral).

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Program Overview

This program is the first in Texas to offer doctoral-level studies in computer science with business training. The emphasis on collaboration with industry and preparation for careers in academia, business, nonprofit organizations and government laboratories is a powerful driver for original research and innovative product development.

Course Work

The program can be taken both full-time and part-time. A total of 54 semester credit hours are required for a student entering with a master's degree and 78 with a bachelor's degree. Course work consists of breadth courses, including 7000-level courses from both concentrations (information management and software systems), and an introduction to a computer science research course. The remainder of the degree consists of the depth electives (7000-level courses from the student's concentration) and dissertation hours. Additional requirements include a qualifying exam, a comprehensive exam, and programming competency skills.

What Our Alumni Say

“I started at Texas State while working full-time because of the flexibility of taking graduate-level evening courses on the Round Rock Campus. I focused on my thesis while working in a research lab on the San Marcos Campus under the guidance of very supportive faculty members.ˮ

— Lee B. Hinkle, M.S. ’16, Computer Science, current student

Program Details

Graduate students consistently win national, regional and industry awards, including National Science Foundation Graduate Research Program Fellowships, Council of Southern Graduate Schools Outstanding Thesis awards, and IBM’s Master the Mainframe contests.

Program Mission

The mission of the Department of Computer Science is to advance the knowledge of computer science and technology through education, research and service for the betterment of society. The program focuses on key areas of applied computing of national priority:

• computer security and networking
• data analytics and management
• high-performance computing
• edge computing
• informatics and smart health
• software engineering

The curriculum emphasizes building complementary and interdisciplinary technical skills in applied computing and equipping students with non-technical skills that are essential to navigating multiple career paths.

Career Options

Program faculty.

The department has the following main research areas: computer security and networking, data analytics and management, high-performance computing, human-computer interaction, informatics and smart health, Edge Computing, and software engineering. With expenditures of $1.5 million in recent years, research activities have increased several-fold, leading to numerous faculty accolades, including a Presidential Early Career Award for Scientists and Engineers (PECASE), several NSF Faculty Early Career Development (CAREER) Awards, Department of Energy (DOE) grants, and multiple Facebook and Google awards.

Contact  The Graduate College  for general questions about getting started with your application, funding your degree, and more. If you have program-specific questions after reviewing the program details, we encourage you to contact the following individuals.

Doctoral Program Director Dr. Anne Hee-Hiong Ngu [email protected] 512.245.3409 Comal (CMAL) , Room 311C

Advisor Support Karen Hollensbe [email protected] 512.245.3409 Comal (CMAL) , Room 211B

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Application Process

Review requirements, submit application, upload documents, check status, application deadlines.

This program's deadline is firm. This type of deadline means the application and other application requirements must be submitted by the program's specified deadline day.

Admission Requirements

The items required for admission consideration are listed below.  Additional information for applicants with international credentials can be found on our  international web pages .

Application

• Completed  online application

Review  important information  about the online application.

Application Fee

• $55 Nonrefundable application fee, OR
• $90 Nonrefundable application fee for applications with international credentials

Review  important information  about application fees.

Transcripts & GPA

Applicants with a bachelor's and master's degree

• baccalaureate degree in computer science or related field from a regionally accredited university (Non-U.S. degrees must be equivalent to a four-year U.S. Bachelor’s degree. In most cases, three-year degrees are not considered. Visit our International FAQs for more information.)
• master's degree in computer science or related field from a regionally accredited university master's degree from a regionally accredited university. (Non-U.S. degrees must be equivalent to a U.S. Master’s degree. Master’s degrees following a three-year Bachelor’s degrees may not be equivalent; please contact [email protected] if you are unsure.)
• a copy of an official transcript from  each institution  where course credit was granted
• competitive GPA, which typically means an overall GPA of 3.3 or higher, in all completed graduate course work.

Applicants with a bachelor's degree only

• baccalaureate degree in computer science or related field from a regionally accredited university
• a 3.0 overall GPA or a 3.0 GPA in your  last 60 hours  of undergraduate course work (plus any completed graduate courses)

Review  important information  about transcripts. Official transcripts, sent directly from your institution, will be required if admission is granted.

Test Scores

• official GRE (general test only) required with competitive scores in the verbal reasoning and quantitative reasoning sections

Approved English Proficiency Exam Scores

Applicants are required to submit an approved English proficiency exam score that meets the minimum program requirements below unless they have earned a bachelor’s degree or higher from a regionally accredited U.S. institution or the equivalent from a country on our  exempt countries list .

• official TOEFL iBT scores required with a 85 overall
• official PTE scores required with a 57 overall
• minimum individual module scores of 6.0
• official Duolingo scores required with a 115 overall
• official TOEFL Essentials scores required 9.5 overall

This program does not offer admission if the scores above are not met.

Review important information about official test scores.

Documents & Other Requirements

• Applicants are independently reviewed and ranked by each member of the admissions committee based on a defined set of criteria. Those that are top-rated will be contacted for an interview via Skype or phone and asked a pre-determined set of questions. Based on the results of the interviews, the committee will rank the applicants again to determine the final list for admission.
• three letters of recommendation submitted directly from professionals who are qualified to assess your academic abilities
• written statement of research interests and goals
• Since admission to this thesis-/dissertation-based program requires an intent to mentor letter (an agreement from one of our faculty members to supervise your research project) as part of the application process, we strongly recommend that applicants contact potential mentors by sending their CV and research interests and securing that agreement prior to submitting an admission application. The department cannot guarantee that a suitable mentor will always be available.

Review important information about documents.

Additional Information

• Application Decisions
• International Applicants
• Reapplication Process

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Academic catalog, ph.d. in computer science.

The doctoral program in computer science provides students with a deep grounding in the fundamental principles and practice of computer science through core and elective coursework. The program also prepares students to conduct novel research that advances the state of the art in the field of computer science.  Students conduct research projects under the direction of a faculty mentor, culminating in the defense of a doctoral dissertation.  Graduates of the program are expected to excel in research, teaching, and the practice of computer science.

Admission Requirements

Applicants must have earned a Baccalaureate degree from an accredited university. Students apply through the Graduate School by submitting an application and the following supporting materials:

• Official transcripts of all previous academic work.
• Applicants from countries where English is not the first language are required to demonstrate English proficiency. Please consult the graduate school website for required scores.
• Personal Statement of Purpose.
• A minimum of two letters of recommendation.
• A CV/resume with evidence of other relevant experience.

Depending on qualifications for study, students may need to complete leveling coursework at the undergraduate level. These courses are not applied towards the degree. Applicants must be able to demonstrate knowledge of programming in a high-level language such as Java or C++, including knowledge of data structures and algorithms. This can be demonstrated by completing CS 2302 Data Structures  with a B or better, or by completing equivalent coursework or certifications as approved by the program committee.  Additional leveling courses may be required as prerequisites for specific graduate courses, or on a case-by-case basis depending on the qualifications of the student.

Degree Requirements

The PhD program requires a minimum of 36 credit hours of coursework beyond the bachelor's degree, and 36 credit hours of research, seminar, and dissertation courses. Students who enter the program with a relevant Master's degree qualify for reduced coursework, with a minimum of 15 hours of coursework. All courses must be taken at the 5000-level or above, unless specifically approved by the graduate advisor; when possible PhD students should take 6000-level courses. The coursework and research credit requirements are summarized in the following table.

Table 1 summarizes the degree requirements. The descriptions follow.

Core Courses (9 credit hours):

The following three (3) core courses are required for all students and must be completed with a B or better.

Breadth Courses (12 credit hours):

To fulfill the breadth requirement, students must complete at least one course from four of the following five areas of computer science.  All courses must be completed with a B or better.

Technical Electives (12) credit hours:

Students must select at least 12 credit hours of technical elective courses in computer science. These courses should be selected in consultation with the research advisor and graduate program advisor to develop technical depth in the student's specific area of research interest.

Interdisciplinary Elective (3) credit hours:

Students must take at least one graduate-level course outside of the computer science department to develop exposure to interdisciplinary topics that complement the student's area of study.

Doctoral Research (27) credit hours:

Students must take at least 27 hours of doctoral research credits.

Dissertation (6) credit hours:

Students must take a minimum of six (6) hours of dissertation credits.  These credits may only be taken after passing the comprehensive examination (dissertation proposal).

The dissertation must demonstrate competence in scholarly exposition and the ability to do independent research. It should present original investigations at an advanced level on a significant problem in computer science and should provide the basis for a publishable contribution to the research literature in the field. The rules for the dissertation and dissertation defense will follow the guidelines set forth by the Graduate School at UTEP.

Doctoral  Seminar (3) credit hours:

Students are expected to actively participate in departmental seminars and other scholarly activities.  During the program, they must complete at least 3 hours of seminar credits.

Students Entering with a Relevant MS Degree

Students entering with a relevant Master's degree must satisfy the core requirements of the PhD program through coursework or transfer credits and must complete a minimum of 15 credit hours of technical coursework in the PhD program.  The specific coursework will be determined in consultation with the graduate advisor.

Examinations

Doctoral students must complete a qualifying examination, a comprehensive examination, and a final dissertation defense.  The detailed requirements for each examination can be found on the departmental website.

The qualifying examination is designed to ensure that students are prepared to conduct research at the PhD level.  This includes assessing graduate-level mastery of fundamental concepts in computer science, as well as written and oral communication skills.

The comprehensive examination is a written and oral defense of a dissertation proposal.  This is designed to ensure that the student has identified a relevant research problem, outlined a feasible and sound approach to address the problem/research questions, and acquired sufficient depth of knowledge in the topic area to perform new and significant research. Upon successful

completion of the examination, the chair of the student's dissertation committee will inform the graduate school that the student is ready to begin work on his or her final dissertation, and the student will be admitted to candidacy.

The culmination of the PhD is writing and defending a dissertation.  Students must submit a written dissertation following the guidelines published by the graduate school and defend the dissertation in a public defense before an approved dissertation committee.

Cybersecurity  Certificate

The department also offers a certificate in cyber security that can be obtained in combination with the PhD degree if the student selects the necessary courses as electives.  See the description of the certificate program for the detailed requirements.

Degree Plan

Required Credits: 72

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• UTCS Direct

This page contains instructions for applying to the UT Austin Department of Computer Science on-campus graduate program.

For general information about our graduate program, please visit our Prospective Students page.

For a list of Frequently Asked Questions, please see out our  Admissions FAQ page.

Looking for application information for the online master’s programs? Visit the Computer & Data Science Online website

Applications for Fall 2024 are closed. Our application for Fall 2025 admission to our PhD and on-campus Masters programs will open October 15, 2024.

We expect to let students who are admitted to the phd program know that they have been admitted by february 2024. admitted master's students will be notified by the end of march, though we hope to inform them sooner if we can. all admission decisions are emailed..

Fall 2024 Application deadline: December 15, 2023 (23:59 CST). Please use this checklist  to ensure that you are submitting all the materials necessary.  Note: For application to the Computer Science graduate program, you are required to submit the following materials via both the ApplyTexas and the CS Department Supplement applications. We recommend starting your application well in advance of the application deadline to ensure that you have sufficient time to submit all materials.

1) Submit via  www.applytexas.org

• Application for admission
• Application fee
• Transcripts (1)  – Within 48 hours of the submission of your application, you will receive an email from the Graduate and International Admissions Center directing you to the  MyStatus  page where you will be asked to upload your transcripts.  Please do not mail these credentials.  For additional information regarding the submission of transcripts to UT-Austin, please see  https://gradschool.utexas.edu/how-to-apply
• Proof of Submission of Department Application: When you complete and submit your CS Department Supplement (outlined in Step 2) print the final submission page to a PDF and return to your MyStatus page to upload this as proof that you completed the Department Supplement.   

2) Submit via  CS Department Supplement :

• Statement of purpose  - Approximately 2 pages describing your reasons for pursuing graduate study and academic and professional interests and goals. This may include events/experiences that prepared you for CS graduate study and how your interests complement the department's faculty and research.
• Transcripts (2)  - The department will not view the transcripts you upload to the MyStatus page; you must provide us with separate copies through the CS Department Supplement.
• Three letters of reference  – You must supply your references’ names and email addresses to the CS Department Supplement [this information is not downloaded from ApplyTexas]. After you provide their contact information, emails will be sent to your references with instructions on how to upload their letters. Letters should emphasize research experience and academic achievements, particularly in computer science. Your references should submit their letters by  December 20, 2023 (17:00 CST)  for full consideration.
• (International students only) TOEFL or IELTS scores
• Optional: GRE scores*, CV and up to three publications. CV should also include a scan of any aid award letter that has award details such as NSF, Fulbright, etc. If you provide GRE scores, you must also have an official score report sent to UT-Austin.

3) An official report of  Graduate Record Examination (GRE)  scores (optional for Fall 2024)*.  Please request that ETS send official test scores to UT-Austin. (UT-Austin code 6882 – you do not need a departmental code).

4) An official score report for the  TOEFL  or  IELTS  (international students only)**. Scores must be sent to the university by the testing agency (self-reported scores are not accepted). The Educational Testing Service (ETS) institution code for UT Austin is 6882. There is no institutional code for the IELTS examination. To fulfill the requirement with scores from the IELTS, please use the IELTS electronic score delivery service to send your scores to the “University of Texas at Austin” account.

*As a temporary accommodation in response to COVID-19, the GRE requirement will be waived for all applicants for the Fall 2024 semester. Students may continue to submit official GRE scores for consideration, but they will not be required to do so. GRE scores when provided, will continue to serve as just one of the many factors considered in our review of a student’s application. Please take into consideration that providing GRE scores can bolster your application if there are aspects of your application that you feel may be not as competitive as others. If you have any questions, please feel free to reach out to us and we can better assist you.

**International applicants who are from a  qualifying country  are exempt from this requirement. Additionally, applicants are exempt from the requirement if they possess a bachelor’s degree from a U.S. institution or a  qualifying country . The requirement is not waived for applicants who have earned a master’s—but not a bachelor’s—degree from a similar institution.

We want to emphasize that all materials should be uploaded electronically. We will carefully dispose of any paper materials we receive, unless we have requested them.

We do not evaluate applications on a rolling basis. An application is evaluated on its own merits and in comparison to all the applications for a given year. Review typically begins in late December, with decisions made by early spring.  

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• College of Science and Engineering
• Department of Computer Science
• Ph.D. Major in Computer Science (Information Management Concentration Entering with Bachelor's Degree)
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• Ph.D. Major in Computer Science (Information Management Concentration Entering with Master's Degree)
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• M.A. Major in Computer Science (Non-​thesis Option)
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• M.S. Major in Computer Science (Software Engineering Concentration Thesis Option)
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Doctor of Philosophy (Ph.D.) Major in Computer Science (Information Management Concentration Entering with Bachelor's Degree)

Program overview.

The Department of Computer Science offers an applied computer science Ph.D. program that incorporates leadership, innovation, and communication skills necessary to prepare students to navigate multiple career environments. The program combines the application of computer science practice and theory. Students are encouraged but not required to take electives in entrepreneurship and commercialization skills. The curriculum is centered on two technical tracks that align with faculty research interests: Information Management and Software Systems. The Information Management track encompasses research topics in data analytics and management, human computer interaction, and informatics. The Software Systems track covers topics in computer security and networking, high-performance computing, and software engineering. In addition, the program has a programming requirement to ensure that students can implement a substantial piece of software.

The program focuses on key areas of applied computing of national priority: data science and machine learning, human-computer interaction, computer vision and multimedia, computer security and networking, high-performance computing, and software engineering and real-time systems.

Educational Goal

Based on the curricular areas and expectations described above, the main educational objectives of the Texas State program are to equip program graduates with:

• technical knowledge in complementary areas of applied computing,
• skills for conducting cutting-edge research that advances the current state-of-the-art in applied computing, and
• leadership, innovation, and communication skills that prepare students to take on challenges in multiple career environments.

Application Requirements

The items listed below are required for admission consideration for applicable semesters of entry during the current academic year. Submission instructions, additional details, and changes to admission requirements for semesters other than the current academic year can be found on The Graduate College's website . International students should review the International Admission Documents page for additional requirements.

• completed online application
• $55 nonrefundable application fee

         or

• $90 nonrefundable application fee for applications with international credentials
• baccalaureate degree in computer science or related field from a regionally accredited university (Non-U.S. degrees must be equivalent to a four-year U.S. Bachelor’s degree. In most cases, three-year degrees are not considered. Visit our  International FAQs  for more information.)
• official transcripts from  each institution  where course credit was granted
• a 3.0 overall GPA or a 3.0 GPA in the last 60 hours of undergraduate courses (plus any completed graduate courses)
• official GRE (general test only) with competitive scores in the verbal reasoning and quantitative reasoning sections
• Since admission to this thesis-/dissertation-based program requires an intent to mentor letter (an agreement from one of our faculty members to supervise your research project) as part of the application process, we strongly recommend that applicants contact potential mentors by sending their CV and research interests and securing that agreement prior to submitting an admission application. The department cannot guarantee that a suitable mentor will always be available.
• three letters of recommendation submitted directly from professionals who are qualified to assess the student’s academic abilities
• written statement of research interests and goals
• Applicants are independently reviewed and ranked by each member of the admissions committee based on a defined set of criteria. Those that are top-rated will be contacted for an interview via Skype or phone and asked a pre-determined set of questions. Based on the results of the interviews, the committee will rank the applicants again to determine the final list for admission.

Approved English Proficiency Exam Scores

Applicants are required to submit an approved English proficiency exam score that meets the minimum program requirements below unless they have earned a bachelor’s degree or higher from a regionally accredited U.S. institution or the equivalent from a country on our  exempt countries list .

• official TOEFL iBT scores required with a 85 overall
• official PTE scores required with a 57 overall
• official IELTS (academic) scores required with a 6.5 overall and minimum individual module scores of 6.0
• official Duolingo scores required with a 115 overall
• official TOEFL Essentials scores required 9.5 overall

This program does  not  offer admission if the scores above are not met.

Degree Requirements

The Doctor of Philosophy (Ph.D.) degree with a major in Computer Science concentration in Information Management requires 78 semester credit hours for students entering with a bachelor's degree, up to 24 hours of which can be from 5000 level master's Computer Science courses (the selection of courses in this category should be made in consultation with the student's Ph.D. advisor and the program director). Students interested in entrepreneurship and commercialization can participate in two boot camps and two entrepreneurship and commercialization courses as electives.

 Only courses which have not been completed in the breadth requirement may be completed in the depth requirement.

 Courses that are already used to satisfy the breadth and technical depth cannot be used for other elective requirements.

Procedures for Prior Learning Assessment Course Credit:

Students in the Ph.D. program in Computer Science can apply up to 12 hours of coursework through a prior learning assessment (PLA) evaluation process when they demonstrate mastery of applicable skills and learning outcomes. PLA course credit can be satisfied through experiential learning students gained through work, non-course-based advanced studies, internships, or externships prior to beginning the Computer Science Ph.D. Program. Note that the total number of credits earned through PLA and course transfer must not exceed 12 semester credit hours (for criteria and processes for earning transfer credit, see the relevant section in the catalog). Students who apply for PLA credit must meet the following conditions:

• Full-time students must make the request for PLA credit in their first year in the program. Part-time students must make the request before completing a total of 18 credits.
• The PLA experiences on which the student is basing the request for PLA credits must have occurred within five years of when the request is made. 

The process of applying for PLA credit includes the following:

• A portfolio of written work is used to evaluate a student’s work and experience for course credit.
• The student provides a summary document that includes the course description for each course for which they are requesting PLA credit, the student learning outcomes for the course (SLOs), and a numbered and detailed explanation of how their experience demonstrates expertise in the subject matter.
• The explanation should include the SLOs for each course under consideration and explicitly map them to parts of the student’s supported materials that demonstrate mastery of the SLO. There should be no “double dipping” of a single aspect of a student’s supporting materials, i.e., materials cannot be mapped to more than one course SLO. In addition, if credit for several courses is requested, a single aspect of a student’s supporting materials cannot be used for more than one course.
• In addition to the summary document, the student will include supporting materials in the form of appendices, which contain reports, peer-reviewed publications, contracts, grant proposals, certificates, official transcripts, etc.

The portfolio is evaluated by a PLA evaluation committee, constituted and chaired by the director of the doctoral program.  In addition to the director of the doctoral program, the committee will include two core doctoral faculty (appointed by the department chair) and one faculty member in the student’s subfield, with appropriate doctoral faculty status.  If one or more of the courses for which the student is requesting PLA credit are not Computer Science courses (e.g., an MSEC course), an external faculty responsible for the non-CS course will be invited to serve on the committee in place of the member representing the student’s subfield.  Approval of the portfolio is required by the doctoral program director and a majority of the evaluation committee. Once approval is recommended by the department, the Ph.D. program director submits a written petition to the Dean of The Graduate College to grant course credit for prior learning assessment. The petition must include the courses for which credit is requested. The petition also includes the decision of the evaluating committee and the summary document created by the student. The appendices are made available on request.

Application for Advancement to Candidacy

When all requirements for admission to candidacy have been met (completion of boot camps, completion of required coursework, passing of the qualifying and comprehensive exams, completion of the programming requirement, and submission of an approved dissertation proposal) the Ph.D. program director forwards the Application for Advancement to Candidacy to the dean of The Graduate College for review and approval. This application form is available on The Graduate College website. 

Grade-Point Requirements for Advancement to Candidacy

A minimum GPA of 3.0 on all coursework undertaken in the doctoral program is required for admission to candidacy. Grades below a B on any graduate coursework cannot be applied toward the Ph.D. degree. Incomplete grades must have been cleared before approval for advancement to candidacy can be granted. No more than six semester credit hours of dissertation research can be taken before advancing to candidacy.

Advancement to Candidacy Time Limit

No credit will be applied toward a student’s doctoral degree for coursework completed more than five years before the date on which the student is admitted to candidacy. This time limit applies to course credit earned at Texas State as well as course credit transferred to Texas State from other institutions.

Dissertation Proposal

The proposal must outline the substance and scope of the planned dissertation research and explain its merits. It has to include at least an introduction, methodology to be used, a survey of the relevant literature, and preliminary results that demonstrate the feasibility. The goal of the proposal is to establish that the student has a sufficient grasp of the fundamentals of the chosen dissertation topic to execute the research.

Comprehensive Examination

The comprehensive examination consists of a written and an oral component.  The qualifying exam serves as the written component. The oral component is administered by the dissertation committee, typically right after the dissertation proposal.  Completion of both the business plan and a grant proposal are required for advancing to candidacy and is part of the comprehensive examination.  

Dissertation Enrollment Requirements

After being admitted to candidacy, students must be continuously enrolled for dissertation hours each fall and spring semester until the defense of their dissertation. At least 18 semester credit hours of dissertation research must be taken after having advanced to candidacy. If a student is receiving supervision on the dissertation during the summer or if the student is graduating in the summer, the student must be enrolled in dissertation hours for the summer. All candidates for graduation must be enrolled in dissertation hours (e.g., CS 7199) during the semester in which the degree is to be conferred, even if they have already satisfied the minimum dissertation hours.

Dissertation Time Limit

Each Ph.D. student must prepare a written dissertation proposal and defend it orally. This should be done by the time the student has completed 36 semester credit hours and after identifying the dissertation committee, passing the qualifying exam, fulfilling the programming requirement, and completing all required courses and boot camps. Any student who does not defend his/her dissertation proposal by the time 45 semester credit hours have been accrued will be dismissed from the program. After advancing to candidacy a student should complete their dissertation within five years, keeping in mind the ten year total time limit.  If the proposal defense is not passed, the student will have the option of taking a second and final defense in the following long semester. Students will be dismissed from the program if they do not pass the proposal defense the second time.

Dissertation Committee

The student, in consultation with his/her dissertation advisor, must establish a dissertation committee that consists of the dissertation advisor, two other doctoral faculty members from the Department, and one faculty member with at least adjunct doctoral faculty status either from another department within the university or from another institution who would be selected based on the relevancy of their research to the student’s dissertation. The dissertation advisor serves as the chair of the committee.

Committee Changes

Any change to the dissertation committee must be submitted using the Dissertation Advisor/Committee Member Change Request Form for approval by the Dean of The Graduate College. Changes must be submitted no later than sixty days before the dissertation defense. The “Dissertation Advisor/Committee Member Change Request form” may be downloaded from The Graduate College’s website.

Dissertation Research and Writing

All doctoral students must complete a dissertation that consists of original research and demonstrates mature scholarship and critical judgment in addition to familiarity with tools and methods in the chosen area. The dissertation project must adhere to the dissertation proposal and cover the topic approved by the student’s dissertation committee.

Dissertation Defense

Once the dissertation has been completed, a final exam (referred to as the dissertation defense) on the dissertation must be conducted. The dissertation defense cannot be scheduled until all other academic and program requirements have been fulfilled. A complete draft of the dissertation must be given to the members of the dissertation committee at least one month before the defense. However, students are highly encouraged to provide drafts earlier so that the committee members can provide feedback, which the student, in consultation with the dissertation advisor, will address in later drafts to ensure that the dissertation is defendable and each committee member is satisfied before the dissertation defense takes place.

The dissertation defense consists of two parts. The first part is a public presentation of the dissertation research. The second part of the defense immediately follows the public presentation. It is restricted to participation of the student’s dissertation committee and entails an oral examination of the dissertation research. Approval of the dissertation requires positive votes from the student’s dissertation advisor and from the majority of the remaining members of the dissertation committee. Notice of the defense presentation will be publicly posted at least two weeks in advance.

If the dissertation defense is not approved, the student will have the option of taking a second and final dissertation defense in the following long semester. Students who do not pass the dissertation defense the second time will be dismissed from the program.

The results of the dissertation defense must be recorded in the Dissertation Defense Report Form and submitted to The Graduate College before the Dean of The Graduate College can give final approval of the dissertation. This form can be downloaded from The Graduate College’s website. The student must submit his/her dissertation to The Graduate College for final approval. The guidelines for submission and approval of the dissertation can be obtained from The Graduate College.

Students must pass the dissertation defense by the time 90 semester credit hours have been accrued. The Ph.D. program director will review each student annually to ascertain his/her progress towards the degree and will consult the student’s dissertation advisor and dissertation committee on this matter as needed. Any student who does not pass the dissertation defense by the time 90 semester credit hours have been accrued will be dismissed from the program.

Approval and Submission of the Dissertation

A final copy of the dissertation proposal, accompanied by the signed approval forms, must be turned in to the Ph.D. program director, who will forward them to the Dean of The Graduate College for review and final approval.

Doctorate level courses in Computer Science: CS

Courses Offered

Computer science (cs).

CS 7100. Graduate Computer Science Internship.

This course provides advanced training supervised by computer scientists in internship programs approved by the department.

CS 7199. Dissertation.

Original research and writing in computer science is to be accomplished under the direct supervision of the Ph.D. research advisor. While conducting dissertation research and writing, the student must be continuously enrolled each long semester. Graded on a credit (CR), progress (PR), no-credit (F) basis. Repeatable for credit. Prerequisite: Instructor approval.

CS 7299. Dissertation.

CS 7300. Introduction to Research in Computer Science.

This credit/no credit course is designed to develop research and communication skills for Ph.D. students. Topics covered include research processes, research methods, ethics, conducting literature review, critiquing papers, preparing research proposals, faculty research presentations, and the software tools and platforms available for conducting applied computing research.

CS 7308. Computer Science Studies.

This course provides foundations in computer science for students entering the doctoral program who may need certain background or leveling coursework. The course does not earn graduate degree credit. lt is repeatable with a different emphasis.

CS 7309. Professional Development of Doctoral Assistants.

This course is designed to equip the doctoral students with skills and an understanding of the proper procedures to be effective doctoral instructional and teaching assistants. This course does not earn graduate degree credit.

CS 7311. Data-Driven Computational Methods and Infrastructure.

This course covers computational and statistical methods for using large-scale data sets (‘big data’) to answer scientific and business questions. It focuses on framing research questions, understanding how data can answer them, and using modern software tools for scalable data storage, processing, and analysis.

CS 7312. Advanced Data Mining.

This course provides in-depth coverage of advanced data mining and information retrieval principles and techniques. It also offers extensive training and practice opportunities in frontier research directions. Prerequisite: CS 5316 with a grade of "B" or better or instructor approval.

CS 7313. Advanced Machine Learning and Pattern Recognition.

This course provides students advanced theoretical and practical skills to learn, design, implement, and apply machine learning and pattern recognition approaches. The students will gain analytical and problem-solving skills by studying machine learning and pattern recognition techniques and applying them to solve real problems.

CS 7314. Bioinformatics.

This course introduces advanced algorithms for data-intensive computational analysis targeting biological applications such as drug response prediction, gene network analysis, and protein/RNA structure prediction. Main techniques include greedy search, linear regression, clustering, network analysis, expectation maximization, and Hidden Markov models, which are widely applicable beyond biological data. Prerequisite: CS 5329 or CS 5369L either with a grade of "B" or better or instructor approval.

CS 7315. Network Science.

This course provides in-depth coverage of the fundamentals and research frontiers of network science. The main topics include mathematical models and computational algorithms for analyzing the structure of complex networks and predicting dynamic processes on networks. Other topics include machine learning and data mining on graphs.

CS 7321. Human Computer Interaction: Concepts, Models, and Methodologies.

This course provides an introduction to Human Computer Interaction (HCI) research, methods, and topics, including fundamentals of user interface and experimental design, usability, evaluation methods, software toolkits for interactive applications, graphics, visualization, mobile design, collaborative and social computing, biological factors, and human computation.

CS 7322. Human Factors and Ergonomics.

This course combines knowledge in the fields of intelligent user interfaces, human factors, ergonomics, and environmental psychology. Topics include HCI principles, human information processing, anthropometry, principles of eye tracking and their effects on human factors research, as well as operations of biometrics systems and human factors influencing those systems.

CS 7323. Image Processing and Computer Vision.

Image Processing and Computer Vision are research areas with a variety of modern applications ranging from the analysis of images and videos to real-time processing of image streams coming from self-driving vehicles and robotic agents. This course will prepare students with advanced state of the art knowledge in those fields. Prerequisite: CS 5329 with a grade of "B" or better.

CS 7324. HCI Paradigms for Animation, Visualization, and Virtual/Augmented Reality.

This course introduces advanced methods for enhancing user experience and presents effective HCI models via computer graphics, imaging, animation, simulation, visualization, augmented reality, and immersive virtual reality. Additionally, the course presents related science and engineering foundations as well as graphic design, cognitive science, and perceptual psychology theories and models. Prerequisite: CS 5329 with a grade of "B" or better or instructor approval.

CS 7331. High-Performance Computing.

This course covers the advanced design, analysis, and optimization of high-performance applications. Topics include high-performance computer architectures, including accelerators and systems-on-chip, performance modeling and benchmarking, data and control dependence analysis, data locality estimation, memory hierarchy management, techniques for exposing parallelism, and code transformations. Different workloads are studied. Prerequisite: CS 5329 with a grade of "B" or better or instructor approval.

CS 7332. Advanced Parallel Computing.

This course covers advanced design of parallel algorithms, performance modeling, parallel hardware, language support for parallel programming, and programming models for shared- and distributed-memory systems ranging from handheld multicore devices to large-scale clusters and accelerators. The students will gain applied knowledge and skills by developing parallel software for multiple platforms. Prerequisite: CS 5351 with a grade of "B" or better or instructor approval.

CS 7333. Advanced Green Computing.

This course covers hardware and software techniques to improve the energy-efficiency of computing systems. Topics include best practices in building energy-efficient data centers and mobile devices, current trends in reducing the energy consumption of processors and storage components, energy-aware resource management, software optimizations, and hands-on experience on power-measurable systems. Prerequisite: CS 5351 and CS 5369Y both with grades of "B" or better or instructor approval.

CS 7334. Scalable Systems for Supercomputing.

This course will teach basic aspects of building a scalable high performance computing (HPC) system. Specifically, it will focus on the design principles for scaling parallel communication and I/O operations for accessing HPC storage using a message-passing programming model. The course will use two large-scale systems—checkpointing for resilience and a parallel file system for storage as use cases to demonstrate how these principles are used in practice. Students will develop components of a scalable system and use software tools to measure and analyze their performance.

CS 7341. Cyberspace Security.

This course presents recent advances in methodologies, models, systems and applications of cyberspace security research. Topics include in-depth coverage of the state-of-the-art security technologies and research issues on information security, software security, network security, secure system design, secure programming, applied cryptography, vulnerability, and threats. Prerequisite: CS 5378 with a grade of "B" or better or instructor approval.

CS 7342. Advanced Computer Networking.

This course covers recent research ideas, methodologies and approaches in networking research. The course focuses on the development of protocols and the analysis of related algorithms. Topics include new network architectures, cloud computing, software defined networking, wireless systems, social networks, and security and privacy. Prerequisite: CS 5310 or CS 5343 either with a grade of "B" or better or instructor approval.

CS 7343. Mobile Networks and Computing.

This course provides an in-depth study of wireless mobile communication networks, wireless network measurements and modeling, channel assignments and coverage, wireless network protocols, mobile data management, wireless security, and various wireless network applications including ad hoc, sensor networks, delay-tolerant networks, and mobile social networks. Prerequisite: CS 5310 or CS 5343 either with a grade of "B" or better or instructor approval.

CS 7351. Advanced Software Engineering.

Software engineering is the application of scientific methods to software development and maintenance. This course provides an in-depth study of advanced concepts and techniques of automatic software generation and analysis. Topics include software process programming, symbolic execution, model checking, property generation and checking, and runtime verification of complex software systems. Prerequisite: Instructor approval.

CS 7352. Real-time Systems.

This course covers issues related to the design and analysis of systems with real-time constraints. The problem of ensuring such constraints is ultimately a scheduling problem, so much attention is devoted to such problems. This course aims to provide a solid foundation for conducting research in real-time systems or related areas.

CS 7387. Research in Computer Science.

This course covers current research topics in computer science under the direction of a supervising professor. Prerequisite: Instructor approval.

CS 7389A. Service Computing.

This course introduces concepts and principles for enabling the development of software as a service based on Service-Oriented Architecture (SOA), methodology of SOA systems development, the main technologies used in achieving SOA, and state of the art techniques and advances in emerging cloud and edge (Internet of Things) services. Prerequisite: CS 5329 with a grade of "B" or better or instructor approval.

CS 7389B. Advanced Software Evolution.

This topics course provides an in-depth study of state-of-the-art software evolution techniques and tools based on the current research literature. Software evolution has become increasingly important in software development. Software systems often evolve to fix defects, to improve performance, or to adapt to various other requirements. Prerequisite: Instructor approval.

CS 7389F. Secure Cyber-Physical Systems: Cryptography and Machine Learning.

This course is designed to introduce students to the fundamentals of cryptography and machine learning and how they can be used to ensure security and privacy in cyber-physical systems (CPS). Topics will include an overview of cyber-physical systems, cryptographic techniques, machine learning algorithms, and security threats and attacks on CPS. The course will also cover privacy-preserving machine learning techniques and design principles for secure CPS. Students who successfully complete this course will be well-versed in cryptography and machine learning approaches for cybersecurity in CPS and be able to use these techniques to address practical real-world issues. Prerequisite: CS 3354 and CS 3358 both with a grade of "D" or better.

CS 7389G. Human-Centered Data Science.

This course is to study the process of deriving insights from data in order to make optimal decisions. Human-Centered Data Science addresses various data science problems with attention to improve the quality of decisions by incorporating human experts in the learning process, e.g., interactive Machine Learning and eXplainable Artificial Intelligence. Prerequisite: CS 3358 with grade of "C" or better.

CS 7389H. Human-Centric Deep Learning.

This course provides an in-depth exploration of deep learning, emphasizing multi-layer neural networks and their applications. Students will explore core topics like convolutional, recurrent, and graph neural networks, along with optimization algorithms and generative models. The curriculum uniquely integrates multimedia processing, Human-Computer Interaction (HCI), and "human in the loop" approaches, demonstrating how deep learning can be applied to image, video, and audio analysis, as well as to create user-centric and interactive systems. Practical aspects, including data preprocessing, model evaluation, and framework implementation, will also be covered, equipping students with the skills to apply deep learning techniques in a human-centered context.

CS 7399. Dissertation.

Original research and writing in computer science is to be accomplished under the direct supervision of the Ph.D. research advisor. While conducting dissertation research and writing, the student must be continuously enrolled each long semester. Graded on a credit (CR), progress (PR), no–credit (F) basis. Repeatable for credit. Prerequisite: Instructor approval.

CS 7599. Dissertation.

CS 7699. Dissertation.

CS 7999. Dissertation.

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Priority application deadline for Fall 2024 admission is Feb 1, 2024. All applicants must contact a doctoral faculty and secure a recommendation letter from a doctoral faculty for the application to be counted as complete

• Degree Requirements
• Candidacy/ Dissertation
• Prior Learning Assessment
• Dissertation Advisor
• Dissertation Committee
• Qualifying Examination
• Programming Requirement
• Comprehensive Examination
• Dissertation Proposal and Proposal Defense
• Dissertation Defense
• Sample Degree Path
• Assistantships
• Scholarships

Each Ph.D. student must prepare a written dissertation proposal and defend it orally. Any student who does not defend his/her dissertation proposal by the time 45 semester credit hours have been accrued will be dismissed from the program. If the proposal defense is not passed, the student has the option of taking a second and final defense in the following long semester. Students will be dismissed from the program if they do not pass the proposal defense the second time.

Dissertation Proposal and Proposal Defense Form:

https://www.gradcollege.txst.edu/forms.html

Sample Degree Paths

Assistantships may be awarded to the most qualified doctoral students. Each doctoral assistant who receives an assistantship will be guaranteed three years of salary as an instructional or teaching assistant (IA/TA) at $32,000 per year for a 50% nine-month appointment as long as adequate progress is being made. Adequate progress is defined as receiving a B or higher in each course and taking at least 9 credit hours in each long semester. Tuition is not included in the assistantship. Currently, Texas State University’s graduate tuition and fees for an 18 semester credit hours per year is around $8000. The latest graduate tuition rate can be found in the following link.

There are a few scholarship opportunities that are dedicated just to Ph.D. students. 

• GAANN Ph.D. Fellowship

The dissertation defense consists of two parts. The first part is a public presentation of the dissertation research. The second part of the defense immediately follows the public presentation. It is restricted to the student’s dissertation committee and all core faculty and entails an oral examination of the dissertation research. Approval of the dissertation requires a positive vote from the student’s dissertation advisor and no more than one dissenting vote from the remaining members of the dissertation committee. Notice of the defense presentation will be publicly posted at least two weeks in advance.

If the dissertation defense is not approved, the student has the option of taking a second and final dissertation defense in the following long semester. Students who do not pass the dissertation defense the second time will be dismissed from the program.

Students must pass the dissertation defense by the time 90 semester credit hours have been accrued. The Ph.D. program committee will review each student annually to ascertain his/her progress toward the degree and will consult the student’s dissertation advisor and dissertation committee on this matter as needed. Any student who does not pass the dissertation defense by the time 90 semester credit hours have been accrued will be dismissed from the program.

Dissertation Defense Report Form:

When all requirements for admission to candidacy have been met (completion of required coursework, passing of the qualifying and comprehensive exams, completion of the programming requirement, and submission of an approved dissertation proposal), the Ph.D. program director forwards the Application for Advancement to Candidacy to the Dean of The Graduate College for review and approval. This application form is available on The Graduate College’s website.

A minimum GPA of 3.0 on all coursework undertaken in the doctoral program is required for admission to candidacy. Grades below a B on any graduate coursework cannot be applied toward the Ph.D. degree. Incomplete grades must have been cleared before approval for advancement to candidacy can be granted. No more than six semester credit hours of dissertation research can be taken before advancing to candidacy. No credit will be applied toward a student’s doctoral degree for coursework completed more than five years before the date on which the student is admitted to candidacy. This time limit applies to course credit earned at Texas State as well as course credit transferred to Texas State from other institutions.

Advancement to Candidacy Form:

Students in the Ph.D. program in Computer Science can apply up to a maximum of 12 hours of coursework through a prior learning assessment (PLA) evaluation process when they demonstrate mastery of applicable skills and learning outcomes. PLA course credit can be satisfied through experiential learning students gained through work, non-course-based advanced studies, internships, or externships prior to beginning the Computer Science Ph.D. Program. There are a limited number of credits that can be earned through PLA and course transfer combined, which depends on the number of credits in the degree program; for the Computer Science Ph.D. the total is 12. Students who apply for PLA credit must meet the following conditions:

• Full-time students must make the request for PLA credit in the student’s first year in the program. Part-time students must make the request before completing a total of 18 credits.
• The PLA experiences on which the student is basing the request for PLA credits must have occurred within five years of when the request is made.

Each Ph.D. student must pass a comprehensive examination (it is a combination of the qualifying exam and the proposal defense). This should be done by the time the student has completed 36 semester credit hours for a student who enters with a master's degree and can only be done after identifying the dissertation committee, passing the qualifying exam, fulfilling the programming requirement, and completing all required courses. Any student who does not pass the comprehensive exam by the time 45 semester credit hours have been accrued will be dismissed from the program. If the comprehensive exam is not passed, the student has the option of taking a second and final comprehensive exam in the following long semester. Students will be dismissed from the program if they do not pass the comprehensive exam the second time.

Comprehensive Exam Form:

Programming requirement.

Extensive programming expertise is essential given the applied focus of the Ph.D. program. Hence, all graduating students must have significant experience in designing and implementing a substantial piece of software, which is defined as a piece of software where the student 1) wrote at least 500 statements, 2) employed at least one non-basic data structure (beyond built-in types, arrays, structs, and vectors), and 3) implemented a non-trivial algorithm (more complex than linear search).

There are several ways to satisfy this requirement. For example, a student can take a course with a project that has a large programming component. Alternatively, the student can satisfy this requirement through programming projects that are, for instance, part of a job in industry, independent research, or his/her dissertation. In any of these cases, the student must obtain a support letter from the course instructor, independent-study advisor, manager, or dissertation advisor with a short explanation of how the three software properties stated above are satisfied. The Ph.D. program director must approve this support letter to certify that the student satisfies the programming requirement, which must be met before the student is allowed to defend his/her dissertation proposal.

Ph.D. students must take the qualifying exam after the required breadth courses and CS7300 are completed. The qualifying exam is a 3-hour written exam that is offered at the beginning of a long semester (only offered in the fall semester currently). Students must answer questions from three of the research areas the Ph.D. program is based on (the number of areas can vary from year to year depending on the availability of faculty). In general, the areas will be 1) Data Analytics and Management, 2) Human-Computer Interaction and Computer Vision, 3) High-Performance Computing, 4) Cyber Security and Networking, 5) Software Engineering and Real-time Systems.

The qualifying examination will take place in the second/third week of the fall semester. At the end of the spring semester, a reading list for each of the exam areas will be made available to the students. Each reading list will include at least five research papers that cover fundamental concepts in the given area. The exam will have at least two questions about each area, except software engineering. The students only need to answer one exam question per area. The exam questions can be as general as explaining how a particular algorithm outlined in a certain paper performs or a critical analysis of the results presented. The grading will be on a scale of 1 to 5. The average score over the three areas must be at least 3 to pass the exam. This is an open book exam. All types of notes are allowed but no electronic devices of any sort are allowed. This means no tablets, cell phones, or computers. Annotated papers are encouraged.

Should a student fail the exam, he/she has the option of taking a second and final qualifying exam at the next offering. Students will be dismissed from the program if they do not pass the qualifying exam the second time.

By the time the student has completed 27 semester credit hours and after the dissertation advisor has been assigned and approved by the Dean of The Graduate College, the student, in consultation with his/her dissertation advisor, must establish a dissertation committee that consists of the dissertation advisor, two other doctoral faculty members from the Department, and one external member that satisfies the eligibility rules of doctoral faculty. This means the member should at least has a terminal degree in computer science or related fields, published an average of 2 papers per year in the last five years,

Dissertation Committee Request Form:

By the time 18 semester credit hours have been accrued, each doctoral student is expected to have secured a qualified dissertation advisor who agrees to advise and mentor the student. The Ph.D. Dissertation/Research Advisor Assignment Form must be completed by the student and the dissertation advisor and approved by the Dean of The Graduate College. This form may be downloaded from The Graduate College’s website.

Dissertation Committee Chair Assignment Form:

Dissertation registration approval form:, candidacy / dissertation.

The goal of the Ph.D. program is to produce well-rounded applied researchers who have demonstrated breadth in computer science, depth in a specific area of concentration, and enhanced abilities in leadership, innovation, and communication. To ensure that these goals are met, doctoral students must fulfill the requirements and pass the exams outlined in this section. Students who do not meet these requirements within the specified timeframes or fail any of the required exams twice will be dismissed from the program.

The requirements, their dependencies, and the expected semester credit hours (SCHs) to fulfill each of the requirements are shown in the below image. Note that only doctoral-level credit hours count toward the listed SCHs for students entering with a master's. For example, master’s-level background courses that a student may want to take are excluded. But some of those courses are counted for students entering with a bachelor's degree. The requirements are discussed in more detail in the following paragraphs. The commercialization courses and boot camps are optional as of Fall 2022. They can be replaced by taking two additional 7000-level classes.

Requirements for doctoral candidacy (dependencies included where applicable)

• Step 1 - Identify dissertation advisor before completing 18 semester credit hours, hereafter referred to as ‘hours’.
• Step 2 - Identify dissertation committee before completing 27 hours.
• Dependency - Must complete 6 hours of commercialization electives or two electives from CS 7000 course list.
• Dependency - Must complete 9 hours of programming electives.
• Dependency for exam - Before the qualifying exam, must complete CS 7300 plus 12 hours of breadth courses.

* Students admitted from an undergraduate program must complete their dissertation proposal before completing 60 hours or face dismissal from the program.

** Students admitted from a graduate program must complete their dissertation proposal before completing 45 hours or face dismissal from the program.

• Step 4 - Advancement to candidacy.
• Dependency - Must complete 24 dissertation hours, up to 6 of these hours may be completed before the dissertation proposal and comprehensive exam.

*** All Doctoral students must defend their dissertation before completing 90 hours or face dismissal from the program.

The main educational objectives of our program are to equip students with

• Technical knowledge in complementary areas of applied computing
• Skills for conducting cutting-edge research that advances the state of the art in applied computing
• Leadership, innovation, and communication skills for multiple career environments

The curriculum emphasizes building complementary and interdisciplinary technical skills in applied computing with the goal of advancing knowledge in a particular field and equipping students with non-technical skills that are essential to navigate multiple career paths. The technical part of the Ph.D. curriculum focuses on applied computing research with two research tracks.

• High-Performance Computing
• Computer Security and Networking
• Software Engineering/Real-time systems
• Data Analytics and Management
• Human-Computer Interaction
• Computer Vision/Multimedia
• CS 7311 Data-driven Computational Methods and Infrastructure
• CS 7312 Advanced Data Mining
• CS 7313 Advanced Machine Learning and Pattern Recognition
• CS 7314 Bioinformatics (NOT OFFERED)
• CS 7321 Human-Computer Interaction: Concepts, Models, and Methodologies
• CS 7322 Human Factors and Ergonomics (NOT OFFERED)
• CS 7323 Image Processing and Computer Vision
• CS 7324 Human-Computer Interaction: Paradigms for Animation, Visualization, and Virtual/Augmented Reality
• CS 7389A Service Computing (NOT OFFERED)
• CS 7389E Network Analysis (counted as CS731X)
• CS 7387 Computer Science Research
• CS 7331 High-Performance Computing
• CS 7332 Advanced Parallel Computing
• CS 7333 Advanced Green Computing
• CS 7341 Cyberspace Security
• CS 7342 Advanced Computer Networking
• CS 7343 Mobile Networks and Computing
• CS 7351 Advanced Software Engineering (NOT OFFERED)
• CS 7389B Advanced Software Evolution (NOT OFFERED)
• CS 7389C Real-Time System (counted as CS735X)
• CS 7389D Scalable Systems for SuperComputing (counted as CS733X)
• CS 7389F Secure Cyber-Physical Systems: Cryptography and Machine Learning (counted as CS734X)
• MSEC 7301 Practical Skills in Commercialization and Entrepreneurship
• MSEC 7302 Leadership Skills in Commercialization and Entrepreneurship
• CS 7300 Introduction to Research in Computer Science
• CS 7100 Internship course (one credit only)
• CS 7309 Professional Development for Instructional Assistant (noncredit course only for students who received assistantships)
• ED 7359 Advanced Quantitative Research Methods
• Math7321 Graph Theory
• Math 7325 Statistics
• Math 7335 Statistics II

Program Overview

The Department of Computer Science at Texas State University is offering a 21st century applied computer science Ph.D. program that incorporates leadership, innovation, and communication to prepare students to navigate multiple career environments. Students are encouraged, but not required to take electives in entrepreneurship and commercialization skills.

The program accepts both full-time and part-time students once per year for fall admission. The priority deadline is Feb 1 and the final deadline for admission is June 1 for international students and June 15, for U.S. students. All applicants must contact a doctoral faculty to secure a recommendation letter from the doctoral faculty for the application to be counted as complete.

The program-specific admission standards include the following.

• All  applicants must have completed a bachelor’s degree in computer science or a closely related discipline. Up to 24 credit hours can be waived for students who enter with a master’s degree in computer science or a closely related discipline.
• Applicants with a bachelor’s degree must have a competitive grade-point average (GPA) on their most recent 60 semester hours of coursework. Applicants with a master’s degree must have a competitive GPA in the MS-level coursework.
• All  applicants must have an official Graduate Record Examination (GRE) submitted to the Texas State Graduate College with competitive scores in the verbal reasoning and quantitative reasoning sections.

In addition, international applicants must submit the following.

• An official diploma or degree certificate and a certified English translation thereof showing the type of degree earned and the date the degree was conferred, as required by The Graduate College from all international applicants.
• If the final degree (bachelor’s or master’s) of the applicant is from a country where English is not the official primary language, the applicant must have a Test of English as a Foreign Language (TOEFL) score of at least 85 or IELTS scores with 6.5 overall and minimum individual module scores of 6.0.
• Proof of sufficient financial resources for their educational and personal expenses as required by The Graduate College from all international applicants. The official offer of a Ph.D. assistantship can be used to satisfy this requirement.

Other requirements include the following.

• Three letters of recommendation must be submitted directly from professionals (university professors or direct supervisors) who are qualified to assess the applicant’s academic abilities.
• A written statement of research interests and goals.
• A complete and up-to-date curriculum vitae (résumé).
• All official academic transcripts from each college or university attended must be sent to the Texas State University Graduate College. Additional details are specified by The Graduate College.
• A completed application (http://www.gradcollege.txstate.edu/programs/cs-phd.html).
• A non-refundable $55 application is required of all applicants.
• An additional international evaluation fee of $35 (in U.S. currency) is required if the application is considered for admission based on foreign credentials.
• Application fee payments can be submitted securely through an online portal or mailed via check/money order in U.S. currency made payable to Texas State University.
• Total of 54 semester credit hours (SCH) for a student entering with a master’s degree and 78 SCH for a student entering with a bachelor’s degree
• 15 SCH required courses (breadth)
• CS7300 Introduction to Computer Science Research (3 SCH)
• Four CS7000-level courses that cover both research tracks (12 SCH)
• 15 SCH elective courses (depth)
• 24 SCH dissertation
• Programming requirement
• Qualifying examination
• Comprehensive examination

More Information

Application for admission

Graduate College

Graduate Courses

Schedule of Courses

Research Information

Ph.D. Unique Features

Ph.D. Video Information

Doctoral Faculty

Current Ph.D. Students

Department of Computer Science

Welcome to the.

Median Salary For Software Developers per U.S. Bureau of Labor Statistics

Graduates Hired By

Google, Microsoft, Amazon, Apple, Nvidia, and many other high-tech companies

1,769 Students

1,038 undergraduate students (including 347 majors and 691 foundational students) and 731 graduate students (including 660 Masters and 71 Ph.D. students) as of Fall 2023

Research Areas

AdVanced Empirical Software Testing and Analysis (AVESTA)

Conducts research in software testing, empirical software engineering, and application of statistical analysis to program analysis

Center for the Science and Engineering of Cyber Security

The objective of the center is to study principles of Cyber Security, how to measure, assess and enforce security in legacy systems, and how to build new systems that are secured.

Data-Intensive Scalable Computing Laboratory (DISCL)

The Data-Intensive Scalable Computing Laboratory (DISCL) has broad research interests in various areas with a focus on building scalable computing systems for data-intensive applications in high-performance scientific computing/high-end enterprise computing.

TTU Wireless Mobile Networking Laboratory (T2WISTOR)

In the TTU Wireless Mobile Networking Laboratory (T2WISTOR), we are conducting research in the areas of Green Networking, Mobile Data Management, Embedded Networked Systems, and Mobile Software.

Ready to apply? Click below to learn more!

Looking For A Scholarship?

Check out the types of scholarships the Edward E. Whitacre Jr. College of Engineering offers!

Department News

April 20, 2024

Jerry S. Rawls Award Recipients Announced

The Edward E. Whitacre Jr. College of Engineering celebrates teaching excellence with the Jerry S. Rawls Distinguished Undergraduate Educator Awards

April 04, 2024

Texas Tech University Professor Akbar Siami-Namin Awarded the Fullbright U.S. Scholar Award for Spring of 2025.

Dr. Akbar Siami-Namin, a professor within the Department of Computer Science has been honored with the 2025 U.S. Scholar Award.

March 13, 2024

Student Organizations of the WCOE Host Engineering Fair

Fueling Futures: TTU Engineering Fair Sparks Creativity and Inspires the Next Generation of Engineers at the Science Spectrum

WCOE Hosts Its Inaugural Research Day Event

Whitacre College of Engineering Ignites Innovation: Inaugural Research Day Sparks Collaboration and Inspires Future Engineers to Shape Tomorrow's World.

Departmental Seminars

Research labs, faculty openings, earn your master's degree in computer science online.

Mold the future of the computer science industry.

What kind of jobs can I get?

Students in our program go on to get jobs such as:

• Software Engineer

• Software Developer

• Computer Scientist

• Web/Mobile App Developer

• Data Scientist Engineer

• Cybersecurity Engineer

• IT Systems Administrators

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Obtaining a Graduate Degree

Your door step to more success..

Students in the Department of Computer Science and Engineering have the opportunity to dive deeper into artificial intelligence, cybersecurity, software engineering, natural language processing, and other research areas that contribute to community and global needs. These programs give students the ability to create a real-world impact within their community.

MS in Computer Engineering has been ranked #19 in 2023  Best Value Computer Engineering Master's Degree Schools

Computer & tech occupations expected to increase by 15% between 2021-2031, faster than average expected growth among all occupations., how to apply.

Prospective graduate students will apply here:  UNT Toulouse Graduate School - Admissions  

For questions or concerns, please  visit FAQs section   to get answers about our graduate programs.

Please review our admission requirements below before you apply.

* Follow this link to submit your supplemental documents for application

Degree programs

Doctoral (phd), ph.d. in computer science and engineering.

An overall evaluation of the student’s credentials is used as a basis for admission. Admission is competitive, and satisfaction of the minimum requirements does not guarantee admission. Click here for more details about the program.

M.S. in Artificial Intelligence

M.s. in computer engineering, m.s. in computer science, m.s. in cybersecurity, m.s. in data engineering.

NOTE: This page's information reflects the most current UNT catalog for incoming graduate students. If you are currently enrolled, please access UNT's  archived degree plans for current students .

Deadline dates for doctoral & masters applicants

To receive full consideration for an assistantship, you must submit your application in ApplyTexas by the following dates:

Spring deadlines

Oct. 15: Priority deadline date to be considered for departmental funding Nov. 5: Hard deadline date

Fall deadlines

Jan. 15: Priority deadline date to be considered for departmental funding

Apr. 15: Hard deadline date for International applicants; Hard deadline to be considered for departmental funding

July 15: Hard deadline date for Non-International applicants

Please check the status of your application at http://my.unt.edu . This is the most current information on your application. It will list any pending information needed.

Due to the large volume of applications received to the department, we do not pre-review applications via email.

Applications are processed by the Graduate School and then forwarded to the department if they meet all the previous departments' requirements.

If it states that the application has been forwarded to the department, it is in committee to be reviewed. Once a decision has been made it will be posted and reflect on http://my.unt.edu .

Calling or writing the department will NOT speed the process. The department will not give you a time frame on when a decision will be made. The department will contact applicants at the email listed on the application if more information is needed.

The department is aware of the appointments that international students make in their countries to receive the proper documentation to attend UNT. Due to the constant change in international law international students need to direct ALL international, I20, and/or VISA questions to the International Advising Department at [email protected] . The CSE department will NOT advise or answer these questions. Information about an applicant will NOT be given out via telephone, so please email the CSE Graduate Coordinator at [email protected]

CSE Grad Orientation

In addition to the UNT Grad Orientation that occurs at the beginning of each semester, the Department of Computer Science & Engineering hosts an orientation for our incoming students to provide a seamless transition into their graduate studies & learn about the resources available to our grads.

Follow the link to access more information on the schedule, presentation, and other resources.

Are you a new international student? Need answers to some questions?

UNT International Affairs has provided  Information for New International Student and Scholar  to assist in the transition process.

Contact the UNT International Affairs office via email & phone.

Email Address: [email protected]

Office Phone: 940-565-2197

• Tuition and Costs
• Frequently Asked Questions
• Graduate School Admissions
• Toulouse Graduate School
• UNT International

Applicant Questions

We require an application from goapplytexas.org , your GRE scores, your English proficiency scores (for international students only), your resume, a copy of your official transcript, and a copy of your undergraduate degree to be considered for any of our graduate programs. Our PhD program also requires 3 Letters of Recommendation and a Statement of Purpose. Here are the typical scores of successful applicants into our programs:

https://computerscience.engineering.unt.edu/sites/default/files/Requirements_for_Admission_8_1.pdf

Official transcripts are sent directly to [email protected] English proficiency test results and GRE scores must be sent directly to UNT from the testing service.

UNT’s school code is 6481

Submit other supplemental documents to the link below. Make sure to input your information correctly, choose your appropriate major, submit your required documents, and other optional documents.

https://engineering.unt.edu/webforms/submission-graduate-application-documents

You can check your student portal at https://my.unt.edu  to see which documents are still needed for your application. Contact the Toulouse Graduate School regarding the status of test scores and transcripts.

Questions along these lines should be directed to our UNT International Office at [email protected]

Due to the high volume of applicants, we do not prescreen any applicants. The department and graduate admissions committee will look at your application when you have properly submitted one through goapplytexas.org .

On average 7-10 business days after submitting your application, you’ll receive an email with instructions on how to set up your student portal on my.unt.edu. This is very important, as you’ll see below. If your transcripts and other academic documents are from a school outside of the US, please upload unofficial scans of your international academic credentials through your myUNT student portal. After you have received your student account activation email, you can log in to your myUNT portal and upload your documents through the Admissions tile or Tasks tile.  Select the document you want to submit and upload it through Add Attachment. We can’t take emailed transcripts, marksheets, or degree certificates. English proficiency test results and GRE scores must be sent directly to UNT from the testing service. UNT’s school code is 6481. Any other supplemental documents will need to be uploaded here: https://engineering.unt.edu/webforms/submission-graduate-application-documents .

Due to the large volume of applications received to the department, we do not pre-review applications via email. Applications are processed by the Graduate School and then forwarded to the department if they meet all the previous departments' requirements. If it states that the application has been forwarded to the department it is in committee to be reviewed. Once a decision has been made it will be posted and reflect on http://my.unt.edu .

Calling or writing the department will NOT speed the process. The department will not give you a time frame on when a decision will be made. The department will contact applicants at the email listed on the application if more information is needed. The department is aware of the appointments that international students make in their countries to receive the proper documentation to attend UNT. Due to the constant change in international law international students need to direct ALL international, I20, and/or VISA questions to the International Advising Department at [email protected] .

You can update/defer the term of entry on your application with the link below.

You cannot update a denied application. If you have been denied previously and you still want your application to be considered, you must reapply and submit an entirely new application. The department and graduate admissions committee will not review a denied updated application.

https://tgs.unt.edu/future-students/graduate-admissions/update-your-application

Due to the high volume of applicants, we do not accept Summer intake applications for international applicants. If you have applied for Summer intake, please update/defer your application to a different term with the link below. When you update your application, you will receive a notification within 7-10 business days. Updating your application does not guarantee a spot within the program.

There are plenty of resources regarding the application process! If you require more information on the general application process and other university information, you can visit the UNT main website at http://www.unt.edu . Information about the Department of Computer Science and Engineering can be obtained from the department web page at http://cse.unt.edu

Yes! When possible, our classes are scheduled on a rotating basis so that every regularly offered class is scheduled at night during any two-year period. Most classes are offered once per year, where the scheduling switches between daytime scheduling and nighttime scheduling on alternate years. To see current course offerings, check your student portal on http://my.unt.edu .

Here are the important application deadline dates:

April 15 th = Fall deadline for full funding consideration

July 15 th = Fall final deadline

October 15 th = Spring deadline for full funding consideration

November 5 th = Spring final deadline

The department provides excellent opportunities for financial support for our best students! The application for departmental financial support is very competitive, and while we support a substantial number of students through assistantships, the number of applications we get is many times the number we can award. In Spring 2022, for example, over 400 students applied for roughly 40 open positions.

However, the Toulouse Graduate School does offer other means of funding to our graduate students. The link below is an excellent resource for graduate students looking for funding outside the department:

https://tgs.unt.edu/future-students/funding

Once you have been admitted into the program, you can enroll in courses at a specific time. Below is a link that gives more details:

https://registrar.unt.edu/when-can-i-register

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ONE OF THE LARGEST CS DEPARTMENTS

Strategically located in the middle of a high technology corridor, which is home to over 1,000s high-tech companies, the UT Dallas Computer Science Department is in the midst of a growth phase that includes expansion of programs in artificial intelligence, machine learning, natural language processing, cyber security, human-computer interaction, autonomous transportation, intelligent traffic systems, data sciences, interactive computing, and more.

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Admission requirements and program policies

This grad track option is a BS to PhD accelerated program for computer science and computer engineering undergraduate students. The student can take a maximum of 12 credit hours of graduate courses while completing the BS degree. These credits will be counted first toward the BS degree and then, upon graduation, be transferred to the PhD degree.

The following is the step-by-step process:

• A student applies for the grad track option in the junior year (having completed at least 75 credit hours with a GPA of 3.5 or higher).
• After the application is approved and the student has completed at least 90 credit hours, the student can start taking graduate courses that are approved for the grad track option as CSE electives for the BS degree requirements. For the graduate courses to be counted toward the PhD degree later, the student should earn a grade of B or higher for the courses.
• The student applies to the Toulouse Graduate School within the first semester of the senior year. Once the student satisfies all course work for the BS degree and having maintained a 3.5 or higher GPA, the student will submit three recommendation letters from faculty members and a statement of purpose to be considered for entry into the PhD program.
• The student must enroll in graduate school in the long semester after finishing his/her BS degree and should take the remaining graduate courses in the following year(s) to complete his/her PhD degree. If the student does not enroll in graduate school in the long semester after finishing his/her BS degree, those graduate course credit hours will no longer be counted for the PhD degree, even if the student comes back for graduate school in the future.
• Once admitted to the PhD program, the students will have higher priority for funding (research and teaching assistantship) to support PhD study.
• TGS will be consulted for cases when students enrolled in the BS program with the BS-to-MS grad track option are transferred to the program with the BS-to-PhD grad track option.

Program requirements

The student is required to take three of the courses listed below in the fourth year of their bachelor’s degree program:

• CSCE 5050 - Applications of Cryptography ( CSCE 4050   )
• CSCE 5200 - Information Retrieval and Web Search ( CSCE 4200   )
• CSCE 5200 - Information Retrieval and Web Search ( CSCE 4930   )
• CSCE 5210 - Fundamentals of Artificial Intelligence ( CSCE 4201   )
• CSCE 5215 - Machine Learning ( CSCE 4930   )
• CSCE 5220 - Computer Graphics ( CSCE 4230   )
• CSCE 5225 - Digital Image Processing ( CSCE 4240   )
• CSCE 5250 - Introduction to Game Programming ( CSCE 4210   )
• CSCE 5255 - Programming Math and Physics for Games ( CSCE 4255   )
• CSCE 5260 - 3D Game Programming ( CSCE 4220   )
• CSCE 5265 - Advanced Topics in Game Development ( CSCE 4250   )
• CSCE 5290 - Natural Language Processing ( CSCE 4290   )
• CSCE 5350 - Fundamentals of Database Systems ( CSCE 4350   )
• CSCE 5380 - Data Mining
• CSCE 5400 - Formal Languages, Automata and Computability ( CSCE 4115   )
• CSCE 5430 - Software Engineering ( CSCE 3444   )
• CSCE 5450 - Programming Languages ( CSCE 4430   )
• CSCE 5460 - Software Testing and Empirical Methodologies ( CSCE 4460   )
• CSCE 5510 - Wireless Communications ( CSCE 4510   )
• CSCE 5520 - Wireless Networks and Protocols ( CSCE 4520   )
• CSCE 5550 - Introduction to Computer Security
• CSCE 5555 - Computer Forensics
• CSCE 5560 - Secure Electronic Commerce ( CSCE 4560   )
• CSCE 5585 - Network Security ( CSCE 4930   )
• CSCE 5610 - Computer System Architecture ( CSCE 4610   )
• CSCE 5620 - Real-Time Operating Systems ( CSCE 4620   )
• CSCE 5640 - Operating System Design ( CSCE 4600   )
• CSCE 5650 - Compiler Design ( CSCE 4650   )
• CSCE 5655 - Principles of Compiler Optimization ( CSCE 4655   )
• CSCE 5730 - Digital CMOS VLSI Design ( CSCE 4730   )
• CSCE 5810 - Biocomputing ( CSCE 4810   )
• CSCE 5820 - Advances in Bioinformatics ( CSCE 4820   )

All remaining courses for  Information Technology, BA    must be completed.

Ph.D. student earns Department of Defense scholarship

Thursday, May 02, 2024 • Brian Lopez : contact

Nolan Gutierrez, a doctoral student in the Department of Computer Science and Engineering at The University of Texas at Arlington, has received a prestigious Science, Mathematics and Research for Transformation (SMART) scholarship from the U.S. Department of Defense (DoD).

“This scholarship will help me pursue a more permanent career within the Department of Defense,” Gutierrez said. “I hope to work with my mentor and their team at the Army Research Lab to delve deeper into my research and propose my own projects that align with their research goals.”

Gutierrez will use the scholarship to build upon research he started last year during an internship with the U.S. Army Combat Capabilities Development Command, or DEVCOM, in the Army Research Lab. Specifically, he will focus on enhancing the adaptability of pan-tilt-zoom (PTZ) cameras through multitask learning.

He will see if training a PTZ control system on a variety of motion profiles—such as square, circular, and straight-line movements, both forward and backward—will improve its adaptability and performance. This approach includes deploying a PTZ-equipped robot in scenarios that mimic real-world operational conditions relevant to the Army.

Gutierrez works with UTA computer science Assistant Professor William Beksi in the Robotic Vision Lab. He is Beksi’s second student in as many years to earn a SMART scholarship, following Minh (Jerry) Tram in 2023.

“Not only does Nolan's SMART scholarship strengthen the ties between the DEVCOM Army Research Lab and UTA, but it also shows UTA's commitment to train and provide the DoD with STEM Ph.D. graduates,” Beksi said.

SMART scholarship recipients earn full tuition, a significant annual stipend and a book and health allowance. They also complete a summer internship at a DoD facility and are assigned an experienced mentor. The full scholarship and other benefits allow participants to focus on complex research to further the DoD’s mission and create a lasting impact. The program is a one-for-one commitment: For every year of degree funding, the recipient commits to working for a year with the DoD as a civilian employee.

- Written by Jeremy Agor , College of Engineering

Texas A&M University Catalogs

Artificial intelligence and machine learning - certificate.

The certificate in Artificial Intelligence and Machine Learning is designed for professionals (engineers, analysts, and researchers across many disciplines) to deliver an introduction to techniques, methodologies, and tools in the area of Artificial Intelligence and Machine Learning.

This graduate-level certificate in Artificial Intelligence and Machine Learning will prepare new and experienced professionals to understand the capabilities of modern Artificial Intelligence methodologies and Machine Learning approaches and to effectively apply them in their respective fields of operation. Individuals who complete the program will be able to analyze statistical analysis and machine learning techniques. They will be able to synthesize, use, and assess appropriate artificial intelligence models to solve real-world problems. They will be able to use and assess state-of-the-art artificial intelligence and machine learning tools and will be able to correctly interpret their findings.

The certificate in Artificial Intelligence and Machine Learning provides a flexible curriculum with focus on an algorithmic and foundational aspects with the possibility to integrate application aspects, such as robotics, natural language processing, pattern matching, and others. Courses will be offered by distance learning to provide a flexible schedule for working professionals. Interactive course work, such as collaborative project work in courses, interactions with classmates and instructors on zoom, chat rooms and discussion boards, will complement traditional learning modules with opportunities to interact with other students and provide networking and cohort opportunities.

This program is approved for delivery via asynchronous and synchronous distance education technology.

Additional courses available with consultation of academic advisor. 

All courses must be completed with a grade of C or above.

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Tyler Resident and UT Tyler May 2024 Graduate Recognized at Regional Scholars Forum

May 14, 2024 | Hannah Buchanan

Vega presented “A Neural Network Approach to Predict Opioid Misuse Among Previously Hospitalized Patients Using Electronic Health Records.” Dr. Robert Schumaker, UT Tyler professor of computer science, served as his faculty mentor.

“We appreciate the opportunity for our students to present at the LSUS Regional Student Scholars Forum,” said Dr. Amir Mirmiran, provost and executive vice president for academic affairs. “We are proud of Lucas and his excellent work, as well his mentor, Dr. Schumaker.”

The forum featured original undergraduate and graduate student research from more than 40 colleges and universities across Arkansas, Louisiana, Mississippi, Oklahoma and Texas. Vega holds a UT Tyler Bachelor of Science degree in computer science and mathematics. He plans to become a statistician.

With a mission to improve educational and health care outcomes for East Texas and beyond, UT Tyler offers more than 90 undergraduate and graduate programs to nearly 10,000 students. Through its alignment with UT Tyler Health Science Center and UT Health East Texas, UT Tyler has unified these entities to serve Texas with quality education, cutting-edge research and excellent patient care. Classified by Carnegie as a doctoral research institution and by U.S. News & World Report as a national university, UT Tyler has campuses in Tyler, Longview, Palestine and Houston.