M.S. Software Engineering
The Master of Science in Software Engineering degree welcomes applicants holding undergraduate degrees in Computer Science, Software Engineering, Computer Information Technology, or those who fulfill specified prerequisites. Our program aims to cultivate expertise, foster comprehension of emerging concepts, address industry demands for software engineering professionals, and equip graduates for advanced studies in Software Engineering. Graduates can pursue diverse career paths in software project management, system design and development, and software quality assurance, ensuring a range of opportunities upon completion.
To be accepted into one of the Computer Science Masters degree programs you must have an undergraduate grade point average (GPA) of at least 3.0 or a GPA of at least 3.0 from your last 60 units of work, as calculated by the CSUN Admissions & Records Office; and in most cases you must take the Graduate Record Examination (GRE). We expect GRE scores in all three sections to be at least or above the 50th percentile. Under some special circumstances, if your GPA is under 3.0 but above 2.5 you can still be admitted into one of the programs, but other parts of the application need to be well-above the minimum requirements.
Applicants with an undergraduate Computer Science degree from an ABET-accredited Computer Science program are not required to provide GRE scores, if their undergraduate GPA is 3.0 or higher. All other applicants must send their GRE scores to CSUN.
All lower division program prerequisite courses need to be completed in order to be considered for admission. The CSUN Admissions Office does not forward applications to the Computer Science Department until it receives all transcripts and supporting documentation. The Computer Science Department does not consider any application until the GRE scores have arrived. Questions regarding arrival of transcripts or GRE scores should be addressed to the CSUN Admissions Office.
Application forms for prospective students can be completed online through Cal State Apply. Application materials are processed through the CSUN University Office of Admissions. Applications are accepted until all positions are full, until the application deadline has been reached, or until the University closes the admission period. Special regulations, including application deadlines, govern applications from non-resident and foreign students.
Students already enrolled at CSUN in another M.S. program may apply for admission to the Computer Science M.S. program by filing a Change of Objective Form. These applications are evaluated in the same way as those received from outside the University.
In order to be admitted to the Computer Science Department, you must first meet the University admission criteria and then be evaluated and recommended by the Department for admission to its program. The Department bases its evaluation on your undergraduate and graduate grade point averages (GPA) and your general Graduate Record Examination (GRE) scores. A statement of purpose is not required for admission, but, if submitted, will be used in the evaluation. Send application materials directly to the CSUN Admissions Office.
Students who are accepted to one of the Computer Science Department's Masters programs, but who have not completed the undergraduate prerequisite material, are admitted program prerequisite pending (PPP). If accepted to one of the graduate programs with PPP status, the following prerequisite courses for that program must be completed, while maintaining at least a 3.0 GPA. You can receive credit for equivalent prerequisite classes taken at accredited colleges or universities outside CSUN. Many of these classes are also available at local community colleges and other nearby universities. Transfer credits will be evaluated by the Department. All 100-level and 200-level prerequisites must be completed, prior to application.
You may take graduate classes while working on your program prerequisites, however, you may not take COMP 696C and COMP 698C before you have completed all program prerequisites.
Also, up to 9 units of graduate level work with a grade of B or better can be transferred from another institution, subject to University and Departmental approvals.
Program Prerequisites for Software Engineering MS Degree
| Units | Course Number(s) | Course Title(s) |
|---|---|---|
| 10 | Math 150A, B | Mathematical Analysis I and II (Calculus) |
| 4 | COMP 110/L | Introduction to Algorithms and Programming |
| 4 | COMP 182/L | Data Structures and Program Design |
| 3 | COMP 222 | Computer Organization |
| 3 | COMP 282 | Advanced Data Structures |
| 3 | COMP 333 | Concepts of Programming Languages |
| 4 | COMP 322/L | Introduction to Operating Systems and System Architecture |
| 3 | COMP 380/L | Introduction to Software Engineering |
| 3 | Math 340 or Math 341 or an undergraduate course covering equivalent topics in statistics | Introductory Probability or Applied Statistics I |
Read M.S. in Software Engineering Program Requirements
Required Courses
The student must complete the following four courses:
The student must complete either a group project or a thesis in the area of Software Engineering.
The student will select four elective Computer Science courses at the COMP 400, 500, or 600 level, excluding at a minimum COMP 450, 480/L, 482, 490/L, 491L, 492, 494, 496ALG, 499, 696, 698 and 699. 400-level courses can count as electives only if they are "approved for graduate credit" as noted in the University Catalog. At least two of these courses must be from the following list of Software Engineering electives:
*Total Units Required for the M.S. Degree in Software Engineering: 30
Research
| Marjan Asadinia | Advanced computer architecture, Memory system architectures, Next-generation storage systems, Systems-on-Chip (SoC) and Networks-on-Chip (NoC), Interconnection networks, and deep learning. |
| Richard Covington | Graphical user interfaces; Computer architectures; Simulation and performance analysis. Fall only |
| Kyle Dewey | Compilers and programming languages; Automated test case generation; software testing; Computer Science education. |
| Mahdi Ebrahimi | Big data management with the focus on large-scale scientific workflows; Big data workflow scheduling; Cloud computing. |
| Rashida Hasan | Data Mining, Machine Learning, Deep Learning, Feature Engineering, Data Preprocessing-Feature selection, feature extraction, and Anomaly/outlier detection. |
| Wen-Chin (Amy) Hsu | Computer Science education; Human-computer interaction; Computing with human factors; Data analysis/science. |
| Maryam Jalalitabar | Network Function Virtualization(NFV); Software Defined Networking(SDN); Virtual Network Embedding(VNE). |
| Xunfei Jiang | Energy-efficient storage system; Thermal-aware resource management; Parallel and Distributed Computing; Cloud computing; Spatial database systems; Data Science. |
| Adam Kaplan | High-performance Computing, Cloud Performance vs. Cost Tradeoff, Embedded/Low-Power Machine Learning. |
| Li Liu | Accessible Computing, Assistive Technology, Data Visualization and Explainable AI, Human-machine Teaming. |
| Robert McIlhenny | High-speed architectures. |
| Katya Mkrtchyan | Computer Vision and Image Processing, Biological Video Analysis - Segmentation, Registration, Tracking. |
| Alex Modarresi | Computer networking and security, IoT and smart systems, Software Define Networking (SDN), and ad-hoc routing protocol. |
| Ani Nahapetian | Mobile and wearable computing; User interface design; Mobile and hardware security; Algorithm design for embedded systems. |
| John Noga | Design and analysis of algorithms. |
| Son Pham | Databases; Design, optimization, OODB. Compilers for natural languages. Spring only |
| Abhishek Verma | Data Science, Big Data Computing, Deep Learning, Computer Vision, Machine Learning, Artificial Intelligence, Robotics, Data Mining, Biometrics. |
| George (Taehyung) Wang | Deep Learning, Semantic Computing, Data Mining. |
| Jeffrey Wiegley | Automated assembly path planning; Geometric shape analysis; Embedded systems; Software and infrastructure applications design. |