Computer Science and Engineering - Graduate Programs
Objective
The purpose of the graduate programs in Computer Science (CS) and Computer Engineering (CpE) is to facilitate the student's continued professional and scholarly development. The Master of Science (M.S.) programs are designed to extend the student's knowledge and emphasize a particular area of concentration. The Master of Software Engineering (SwE.) program is designed to provide the student with the opportunity for professional development in the software engineering field. Students who have completed a bachelor's degree in CS, CpE or closely related fields wishing to pursue a doctoral degree may apply for admission in the B.S. to Ph.D. track. The admission requirements to this highly competitive track are the same as those for "advanced admission" (see B.S. to Ph.D. Accelerated Programs). The Doctor of Philosophy (Ph.D.) programs are designed to prepare the student to conduct research and development in an area of concentration.
Areas of study include
- Systems and Architecture: parallel processing, cloud computing, distributed systems, scheduling and load balancing, computer architecture, tools for parallel programming, performance evaluation, fault-tolerant computing, real-time systems, embedded systems;
- Intelligent Systems and Robotics: machine learning, robotics, pattern recognition, multi-agent environments, assistive technologies, human-centered computing, decision support, health informatics, bioinformatics;
- Software Engineering: software life cycles, agile methodologies, formal specifications, object-oriented software engineering, design methodologies, software testing, software evolution, software re-engineering, software processes;
- Database and Data Analysis: spatio-temporal data, data mining, big data analysis, database models and languages, indexing and hashing techniques, conceptual modeling, data security, query optimization, user interfaces, ontologies, Web search and ranking, social networks;
- Networking and Security: sensor networks, wireless networks, information security, secure programming, mobile and distributed computing, multimedia systems, pervasive computing, networking architectures.
For a complete list of graduate programs and disciplines please refer to http://cse.uta.edu/graduate/
Admission
The CSE graduate admission committee bases its decision for M.S. graduate admission on the following criteria (in no specific order):
- An overall GPA of 3.0 or higher in undergraduate coursework.
- A GPA of 3.2 or higher on CS/CpE/SwE related coursework in the last two years of undergraduate degree.
- Relevance of the student's degree (background) to the CS/CpE/SwE curriculum.
- Rigor of the student's bachelor's degree. A four-year degree is considered more rigorous than a three-year degree.
- Reputation of the university/college that the student has received his/her previous degrees from.
- GRE Test: Admitted students typically earn the following scores on the GRE
- GRE quantitative score of at least 155 for MS
- GRE verbal score of at least 145 for MS
- A sum of verbal and quantitative GRE scores of at least 300 for MS.
- International applicants test of English as a Foreign Language (TOEFL) score of 90 or higher on the IBT or a score of 7.0 or higher on the IELTS.
Applicants for the MS degree with (or completing in the near future) a BS in CS, CpE or SwE from UT Arlington and a GPA of at least 3.2 should contact the graduate advisor regarding a GRE waiver. Those with a GPA of at least 3.5 should contact the graduate advisor regarding nomination for Advanced Admission (i.e. admission without application and fee). The GRE waiver may be extended to include non-UT Arlington candidates that have undergraduate degrees in CS, CpE or SwE (with GPA of 3.2 or above) from reputable universities with an ABET accredited program or other select universities subject to graduate advisor's approval.
The above criteria are used as follows in relevance to the three possible admission decisions, i.e., Unconditional Status; Probationary Status; and Denied.
- Unconditional Status: Applies to an applicant who meets the first six criteria above to a degree satisfactory to the graduate admissions committee.
- Probationary Status: Applies to an applicant who meets at least five of the six criteria to a degree satisfactory to the graduate admissions committee and whose record shows promise for success in the program or to an applicant who does not fulfill all the deficiency course requirements.
- Denied:Applies to an applicant who does not meet five of the first six criteria to a degree satisfactory to the graduate admissions committee.
Waiver OF Graduate Record Examination
Upon recommendation of the Graduate Advisor, outstanding UT Arlington graduates may qualify for waiver of the requirements for the Graduate Record Examination (GRE). To qualify, the applicant must meet the following minimum requirements:
- The student must have graduated from a commensurate bachelor's degree program at UT Arlington no more than three academic years prior to admission to the graduate program (as measured from the start of the semester for which admission is sought). A commensurate bachelor's degree program is one that is a normal feeder program for the master's degree program to which the student seeks admission. Undergraduate students in their final year of study are also eligible; in such cases, admission with the GRE waiver is contingent upon successful completion of the bachelor's degree.
- as calculated for admission to the Graduate School ;
- overall;
- in the major field; and
- in all upper-division work.
- The student's UT Arlington grade-point average must equal or exceed 3.0 in the following calculations:
Applicants qualifying for waiver of GRE who do not qualify for advanced admission, must comply with all other requirements for admission, i.e., submitting the application for admission, paying fees, providing official transcripts from other institutions, and meeting any requirements established by the admitting graduate program. The GRE waiver must be recommended by the Graduate Advisor at the time of admission. The waiver of GRE program applies to applicants for master's degree programs only. Some programs may require higher grade-point averages to qualify and some will not waive the GRE under any circumstances.
Additionally, some programs may waive the GRE requirement for non-UT Arlington graduates who seek admission as a master's student and meet qualifications listed in those programs' specific admission requirements. Such waivers are not offered by all graduate programs.
Degree Requirements
Master of Science in Computer Science - Thesis
The Master of Science in Computer Science degree program is designed to develop the scholarship and research skills of the student. Thirty-one credit hours, which include one orientation seminar credit and six thesis credits, are required.
Master of Science in Computer Engineering - Thesis
The Master of Science in Computer Engineering, which is intended for students with a baccalaureate degree in engineering, requires 31 credit hours of which one is orientation seminar and six are thesis credits, and is designed to develop the scholarship and research skills of the student.
Master of Science in Computer Science - Non Thesis
The Master of Science in Computer Science non-thesis options provide professional development in computer science. The structured option requires 37 credit hours of which one is orientation seminar.
Master of Science in Computer Engineering - non thesis
The Master of Science in Computer Engineering non-thesis options are intended for students with an engineering baccalaureate degree. The structured option requires 37 credit hours of which one is orientation seminar.
Master of Software Engineering - Non Thesis
The Master of Software Engineering provides professional development in software engineering. The program requires 37 credit hours of which one is orientation seminar. It includes a 2-course sequence devoted to implementation of a software project.
Admission
The CSE graduate admission committee bases its decision for Ph.D. graduate admission on the following criteria (in no specific order):
- An overall GPA of 3.0 or higher in undergraduate coursework.
- A GPA of 3.2 or higher on CS/CpE/SwE related coursework in the last two years of undergraduate degree.
- For students holding an M.S. degree, similar criteria apply.
- Relevance of the student's degree(s) (background) to the CS/CpE/SwE curriculum.
- Rigor of the student's bachelor's degree and M.S. degree if applicable..
- Reputation of the university/college that the student has received his/her previous degrees from.
- GRE General Test: Admitted students typically earn the following scores on the GRE
- GRE quantitative score of at least 160 for PhD
- GRE verbal score of at least 150 for PhD
- A sum of verbal and quantitative GRE scores of at least 310 for Ph.D. applicants.
- For Ph.D. applicants, three letters of recommendation are needed, as well as a statement of purpose. These should be addressed to Head of Ph.D. Admissions and emailed to: csephd@uta.edu
- For Ph.D. applicants, the following are optional. Meeting these criteria will improve both a student's chances of securing admission and receiving financial support.
- Publication in scholarly conferences/journals.
- A percentile of 80 score or higher on the Computer Science subject GRE.
The above criteria are used as follows in relevance to the three possible admission decisions, i.e., Unconditional Status; Probationary Status; and Denied.
- Unconditional Status: Applies to an applicant who meets the first six criteria above to a degree satisfactory to the graduate admissions committee.
- Probationary Status: Applies to an applicant who meets at least five of the six criteria to a degree satisfactory to the graduate admissions committee and whose record shows promise for success in the program or to an applicant who does not fulfill all the deficiency course requirements.
- Denied:Applies to an applicant who does not meet five of the first six criteria to a degree satisfactory to the graduate admissions committee.
REQUIREMENTS FOR BS TO PHD ACCELERATED PROGRAM
- An undergraduate degree in CS or CpE or closely related field.
- An overall GPA of 3.0 or higher in undergraduate coursework.
- A 3.2 grade point average (on a 4.0 scale) on the last two years of undergraduate course-work. In particular, performance on CS/CpE related courses are emphasized.
- Rigor of the student's Bachelors degree. A three-year degree is not considered rigorous enough.
- Reputation of the University/College that the student has received his/her previous degrees from.
- GRE quantitative score - 160 or higher
- GRE verbal score - 150 or higher
- A sum of verbal and quantitative scores of 310 or more on the GRE1 :
- (International Applicants)
A Test of English as a Foreign Language (TOEFL) score - 90 or higher (iBT)
Continuation
To fulfill its responsibility to graduate highly qualified professionals, the Department has established certain requirements that must be met by students continuing in the graduate programs. In addition to the requirements of the Graduate School listed elsewhere in the catalog, the Computer Science and Engineering Department has established additional requirements detailed in its Guide to Graduate Programs.
Assistantships
Students admitted without any probation may qualify for financial support of the following forms:
- Graduate Teaching Assistant (GTA)
- Graduate Research Assistant (GRA)
- Priority is given to PhD students.
Degree Requirements
B.S. to Ph.D. Track
The B.S. to Ph.D. track in Computer Science or Computer Engineering requires 30 credit hours with 21 hours of diagnostic requirements and nine hours of advanced research-oriented coursework. This is in addition to the Ph.D. requirements.
Ph.D. (Computer Science)
The Ph.D. in Computer Science continues the development of the student's research capability for students who already have an MS degree. Coursework selection in each student's program is designed to support the dissertation area selected by the student.
Ph.D. (Computer Engineering)
The Ph.D. in Computer Engineering is available to students with a prior degree in engineering. It contains essentially the same requirements as the Ph.D. (Computer Science) degree except that it permits interdisciplinary research between Computer Science and one or more of the various engineering disciplines.
For all programs, a minimum of two semesters of full-time study is required during the dissertation phase. There is no foreign language requirement.
Graduate Certificate in Big Data Management and Data Sciences
Program Objective
The Graduate Certificate in Big Data Management and Data Sciences is intended to give those who successfully complete it:
- an ability to understand fundamental concepts of big data management and data sciences, such as data storage and management, and data analysis and mining.
- knowledge of current topics in large scale data analysis, such as relational and non-relational data management, big data analytics, data mining, machine learning, cloud computing, software tools for big data, Web data, and social and information networks.
- an ability to apply this knowledge to subject areas such as business analytics, computational science, health informatics and bioinformatics, and social networks data.
Admission Requirements
Students are required to have an undergraduate preparation equivalent to a baccalaureate degree in Computer Science or Computer Engineering or in a technical field relevant to the CSE curriculum. Students without a proper academic background, as determined by the graduate advisor at the time of the admission review, will be required to complete all assigned deficiency courses with passing grades (in addition to the normal graduate certificate courses). The required foundation (deficiency) courses (the name is followed by the UTA course number) are:
- C Programming (CSE 1320)
- Discrete Structures (CSE 2315)
- Theoretical Computer Science (CSE 3315)
- Algorithms & Data Structures (CSE 2320)
Those who desire to complete the certificate program without enrolling in a graduate degree program must be admitted to UTA as a non-degree seeking student. If these students choose to enroll in the CSE graduate degree program later, their course non-foundation credits can be used to satisfy their MS degree requirements. Note that, for admission to the MS degree program, all UTA and CSE graduate admission requirements, including GRE and GPA, would need to be met.
A one-page essay detailing the applicant’s interest in big data management and data sciences and his/her expected benefit from completing this program.
Two recommendation letters explaining how the applicant will benefit by completing this program and commenting on prospective student's ability to complete the coursework.
Academic Requirements
Students must choose one concentration track: Big Data Management or Data Sciences. Students must complete 15 hours of coursework (5 courses) from those listed below, based on their chosen track. All courses used to satisfy the certificate requirements must be passed with a grade of C or better and the overall GPA must be 3.0 or higher. Alternate courses may be substituted based on consultation with the graduate curriculum advisors in the program.
15 hours from the following list: | ||
CSE 5301 | DATA ANALYSIS & MODELING TECHNIQUES | 3 |
CSE 5330 | DATABASE SYSTEMS | 3 |
CSE 5331 | DBMS MODELS AND IMPLEMENTATION TECHNIQUES | 3 |
CSE 5333 | Cloud Computing | 3 |
CSE 5334 | DATA MINING | 3 |
CSE 5335 | WEB DATA MANAGEMENT | 3 |
CSE 5339 | SPECIAL TOPICS IN DATABASE SYSTEMS 1 | 3 |
CSE 6331 | ADVANCED TOPICS IN DATABASE SYSTEMS | 3 |
CSE 6339 | SPECIAL TOPICS IN ADVANCED DATABASE SYSTEMS 2 | 3 |
CSE 6363 | MACHINE LEARNING | 3 |
1 | This course may be taken when the topic is Data Management for Big Data or Health Informatics. |
2 | This course may be taken when the topic is Advanced Data Mining or Data Exploration. |
This certificate is structured around two tracks:
Big Data Management:
- 2 required core courses: CSE5339 - Special Topics in Database Systems (Data Management for Big Data), CSE5333 - Cloud Computing.
- 3 electives from the following 6 courses: CSE5330 - Database Systems, CSE5331 - DBMS Models and Implementation Techniques, CSE5334 - Data Mining, CSE5335 - Web Data Management, CSE6331 - Advanced Topics in Database Systems (Mining, Stream/Complex, Cloud), CSE6339 - Special Topics in Advanced Database Systems (Data Exploration).
Data Sciences:
- 2 required core courses: CSE 5334 - Data Mining, CSE 6363 - Machine Learning.
- 3 electives from the following 6 courses: CSE5301 - Data Analysis and Modeling Techniques, CSE5333 - Cloud Computing, CSE5339 - Special Topics in Database Systems (Health Informatics), CSE5362 - Social Networks and Search Engines, CSE6339 - Special Topics in Advanced Database Systems (Advanced Data Mining), CSE6339 - Special Topics in Advanced Database Systems (Data Exploration).