Feb 20, 2026  
Graduate Record 2025-2026 
    
Graduate Record 2025-2026

Computer Science, M.C.S.


Return to: School of Graduate Engineering and Applied Science: Degree Programs   


DEPARTMENT OF COMPUTER SCIENCE DEGREES


MASTER’S DEGREE - MCS

Computer Science
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The Master of Computer Science (M.C.S.) degree offers two options: 

  • M.C.S. (coursework) focuses on coursework only: the student performs no independent research. 

  • M.C.S. (project) involves a project: The student conducts independent research overseen by a professor. The level of research effort is commensurate with one (1) typical academic course. 

An M.C.S. student is assigned an academic advisor upon entering the program. If the student selects an M.C.S. (project) degree, their research advisor then becomes the academic advisor. 

M.C.S. General Degree Requirements:

  • An M.C.S. degree requires a minimum of 31 graded, graduate-level credits. Only courses 6000 and above fulfill the department’s M.C.S requirement. 6 credits of non-CS 5000 level courses may be used to count towards the M.C.S. degree. Courses must be approved by the advisor and the Master’s Program Graduate Director (MGPD). 

  • A graded credit means that the course resulted in a letter grade (A, B, C…) as opposed to an audited course (AU) or a pass/fail or credit/no credit course (CR/NC). 

  • No grade lower than a “B” will be accepted towards satisfying the M.C.S.’s degree requirements. While a course with a passing grade lower than B will count in the GPA, it will not count toward degree requirements. 

M.C.S. Degree (Coursework) – 31 credits: 

  • 1 credit of CS 6190 (Computer Science Perspectives). 

  • 12 credits of graded, graduate-level CS breadth electives comprised of a minimum of 3 credits in any four of the six breadth areas listed below (graduate–level 6000 and above). 

  • 18 credits of graded, graduate-level CS electives or other graduate courses approved by the advisor and the MGPD (graduate-level 6000 and above). 

  • At most 3 credits of CS 6993/7993 (Independent Study) may count toward the degree. 

  • CS 8897/9897 (Graduate Teaching Instruction) can be used to satisfy the full-time requirement. 

  • Program Assessment Forms: Engineering Graduate Plan of Study Assessment, Engineering Design Assessment, and Engineering Analysis  

M.C.S. Degree Project (31 credits):

  • M.C.S. Degree (Project) – 31 credits: 

  • 1 credit of CS 6190 (Computer Science Perspectives). 

  • 12 credits of graded, graduate-level CS breadth electives comprised of a minimum of 3 credits in any four of the six breadth areas listed below (graduate–level 6000 and above). 

  • 15 credits of graded, graduate-level CS electives (or other graduate courses approved by the advisor and the MGPD (graduate-level 6000 and above). 

  • 3 credits of CS 7995 (Supervised Project Research) must be taken with the research advisor. These 3 credits reflect the execution, summary report, and presentation of the M.C.S project. CS 8999 (Thesis) cannot be used. 

  • Program Assessment Forms: Engineering Design Assessment Form, Engineering Analysis Form, and Engineering Oral 

  • The assessment for the M.C.S (project) requires a written project description and an oral presentation before a minimum of two CS faculty. 

TRANSFER CREDITS


Students should consult “Transfer Credits” in the School of Engineering and Applied Science—Academic Rules section of the Record for information about transferring courses toward their graduate degree.  

Whether any individual transfer course counts toward CS master’s degree requirements is determined by the MGPD.


 

BREADTH AREAS and COURSES (6000 level and above)


 

1. Cyber Physical Systems, Internet of Things, Embedded Systems


2. Machine Learning, Natural Language Processing, Information Retrieval, Text Mining, Data Mining


  • Credits: 3
  • Credits: 3
  •       Approved Topic: Deep Learning for Visual Recognition (Ordonez-Roman)

          Approved Topic: Learning Theory (Diochnos)

          Approved Topic: Statistical Learning and Graphical Models (Hassanzadeh)

          Approved Topic: Tensors for Data Science (Sidiropoulos)

          Approved Topic: Natural Language Processing (Ji, Meng)

          Approved Topic: Data Mining -  Principles and Algorithms (Zhang)

          Approved Topic: Mining Text Data for Knowledge Discovery (Wang)

          Approved Topic: Reinforcement Learning (Wang, Wei)

          Approved Topic: Vision & Language (Ordonez-Roman)

          Approved Topic: Topics at the Interface of Learning and Game Theory (Xu)

          Approved Topic: Information Retrieval (Wang)

          Approved Topic: Geometry of Data (Fletcher)

          Approved Topic: Digital Image Processing (Zhang)

          Approved Topic: AI for Social Good (Doryab)

          Approved Topic: Machine Learning in Image Analysis (Zhang)

          Approved Topic: Interpretable Machine Learning (Ji)

          Approved Topic: Learning in Robotics (Behl)

          Approved Topic: Topics in Reinforcement Learning (Zhang)

          Approved Topic: Digital Signal Processing (Fletcher)

          Approved Topic: Program Analysis for ML and ML for Prog Analysis (Elbaum)

          Approved Topic: Learning for Interactive Robots (Kuo)

          Approved Topic: Risks and Benefits of Generative AI and LLMs (Evans, Qi)

          Approved Topic: Responsible AI: Privacy, Fairness, and Robustness (Fioretto)

          Approved Topic: Probabilistic Machine Learning (Farnoud)

          Approved Topic: 3D Computer Vision (Cheng)

          Approved Topic: Graph Machine Learning (Chen)

          Approved Topic: Machine Learning for Software Reliability (Wang)

          Approved Topic: Neural Networks (Daneshmand)

          Approved Topic: Analyzing Online Behavior for Public Health (Kautz)

          Approved Topic: Machine Learning on Graphs (Li)

          Approved Topic: Graph Mining (Li)

  • Credits: 3
  • Credits: 3
  •       Approved Topic: Advanced Natural Language Processing (Ji)

          Approved Topic: Advanced Topics in Deep Learning (Qi)

          Approved Topic: Advanced Topics in Machine Learning (Ji)

3. Security, Privacy, Cryptography


  • Credits: 3
  • Credits: 3
  • Credits: 3
  •       Approved Topic: Software Security via Program Analysis (Kwon)

          Approved Topic: Cryptography (Mahmoody)

          Approved Topic: Software Security (Kwon)

          Approved Topic: Defense Against the Dark Arts (Davidson)

          Approved Topic: Advanced Topics in Cryptography (Wu)

          Approved Topic: Cyber Forensics: Automated Software Approaches (Kwon)

          Approved Topic: Hardware Security (Venkat)

          Approved Topic: Network Security and Privacy (Sun)

          Approved Topic: Computer Security: Attacks and Defenses (Davidson)

          Approved Topic: Data Privacy (T. Wang)

          Approved Topic: Threat Detection and Response (Ul Hassan)

          Approved Topic: Responsible AI: Privacy, Fairness, and Robustness (Fioretto)

          Approved Topic: Risks and Benefits of Generative AI and LLMs (Evans, Qi)

          Approved Topic: Economics of Distributed Systems (Ferreira)

          Approved Topic: Software Security Testing (Davidson)

          Approved Topic: Machine Learning in Systems Security (Ul Hassan)

  • Credits: 3
  •       Approved Topic: IoT Security and Privacy (Tian)

4. Theory and Algorithms


5. Computer Systems


  • Credits: 3
  • Credits: 3
  • Credits: 3
  • Credits: 3
  • Credits: 3
  •       Approved Topic: Data-Centric System Design (Khan)

          Approved Topic: Learning and Prediction in Architecture (Khan)

          Approved Topic: Hardware Security (Venkat)

          Approved Topic: Computer Networks (Sun)

          Approved Topic: Network Security and Privacy (Sun)

          Approved Topic: Advanced Embedded Computing Systems (Alemzadeh)

          Approved Topic: Computer Architecture: Hardware Accelerators (Skadron)

          Approved Topic: Software-Defined Networking and Prog Networks (Kim)

          Approved Topic: Cloud System Reliability (Lou)

          Approved Topic: Modern Computing Architectures (Jog)

          Approved Topic: GPU Architectures (Jog)

          Approved Topic: CPU/GPU Memory Systems and Near-Data Processing (Skadron)

  • Credits: 3

6. Software Engineering