MS Program Specializations

Zoom image: The NYCE project team celebrates its CSE Demo Day Spring 2023 first-place award with CSE 611 advisor Alan Hunt. Photo credit: Ken Smith The NYCE project team celebrates its CSE Demo Day Spring 2023 first-place award with CSE 611 advisor Alan Hunt. Photo credit: Ken Smith.

As the field of computer science evolves, our department continues to lead and grow with innovative academic specializations.

Choose from a range of specializations or build your own. This flexibility sets UB apart from other computer science and engineering programs by allowing students to deepen their expertise in high-demand areas across computing and technology and to tailor their degree to their interests and career goals. To choose a specialization, students only need to complete the required courses.

Students enrolled prior to Fall 2026

Students enrolled in the MS Computer Science and Engineering program prior to Fall 2026 may take advantage of the updated curriculum by changing their track to any of our new optional specializations. Interested students should contact csegradcoord@buffalo.edu. Students may not extend their study to pursue a specialization.

Program Specializations

AI and Machine Learning

What you will learn: Deep learning, advanced machine learning, reinforcement learning, computer vision and image processing, and pattern recognition.

Where this specialization will take you: Data science, intelligent systems, and AI-driven research.

Computer Security and Privacy

What you will learn: Network security, software security, and applied cryptography and computer security.

Where this specialization will take you: Cybersecurity, ethical hacking, and digital forensics.

Computer Vision and Image Processing

What you will learn: Computer vision, pattern recognition, biometrics image analysis, and computational vision. 

Where this specialization will take you: Visual intelligence, AR/VR, and automation.

Database Systems

What you will learn: Data models and query languages, distributed systems, database systems, and programming languages. 

Where this specialization will take you: Big data engineering, analytics, and search technologies.

Distributed Systems and Networks

What you will learn: Distributed systems, modern network concepts, data-intensive computing, high-performance computing, and parallel algorithms. 

Where this specialization will take you: Cloud infrastructure, scalable computing, and systems design.

Embodied AI

What you will learn: Robotics algorithms, advanced robotics and human-robot interaction, deep learning, machine learning, reinforcement learning, and computer vision.

Where this specialization will take you: Robotics and autonomous systems, systems design, linguistics and translation, construction, manufacturing.

High Performance Computing

What you will learn: High-performance computing and algorithms and modern computing systems.

Where this specialization will take you: Cloud infrastructure, scalable computing, and systems design.

Information Retrieval

What you will learn: Natural language processing and text mining, information retrieval, and processing of strings and sequences. 

Where this specialization will take you: Big data engineering, analytics, and search technologies.

Programming Language Design

What you will learn: Programming languages and programming language theory. 

Where this specialization will take you: Software architecture, compiler development, and academic research.

Pure and Applied Logic

What you will learn: Programming language theory, database systems, and the theory of computation.

Where this specialization will take you: Software architecture, compiler development, and academic research.

Software and Hardware Systems

What you will learn: Distributed systems, database systems, and computer architecture. 

Where this specialization will take you: Autonomous systems, automation engineering, and mechatronics.

Curriculum Overview

The Computer Science and Engineering MS programs requires 30 credit hours. The curriculum consists of four breadth computer science courses, three focus courses that may be used to form a specialization, and three electives, at least one of which must be offered by CSE.

Students must also complete a capstone course that brings together concepts from across the degree into a single, semester-long group project. An approved capstone may serve as a focus or elective course.

Learn more

Specializations Checklist

CSE MS Program 2026 Specializations checklist

Breadth Requirements

  • CSE 521: Operating Systems
  • CSE 531: Analysis of Algorithms
  • CSE 565: Computer Security
  • CSE 574: Introduction to Machine Learning

Focus Requirements

Complete three CSE 500- or 600-level courses. Select courses within a focus area to complete a specialization. The following courses are excluded from satisfying the Focus requirement:

  • CSE 501: Introduction to Graduate Study in Computer Science I
  • CSE 502: Introduction to Graduate Study in Computer Science II
  • CSE 503: Computer Science for Non-Majors
  • CSE 504: Computer Science for Non-Majors II
  • CSE 508: Programming with Python
  • CSE 510: Special Topics (except when noted in the class syllabus)
  • CSE 542: Software Engineering Concepts
  • CSE 544: Machine Learning and Society for Non-Majors
  • CSE 578: Computational Investment
  • CSE 598: Internship
  • CSE 610: Special Topics (except when noted in the class syllabus)
  • CSE 611: MS Project Development

Capstone Requirement

Complete one capstone course from the following list and achieve a B- or better. A capstone course may also be used to satisfy a Focus or Elective requirement. Your capstone course should be taken in your final semester.

  • CSE 518 Software Security
  • CSE 548: HPC II
  • CSE 562: Database Systems
  • CSE 573: Computer Vision
  • CSE 586: Distributed Systems
  • CSE 605: Advanced Concepts in Programming Languages
  • CSE 635: Natural Language Processing and Text Mining
  • CSE 676: Deep Learning

A supervised project can also be used to satisfy the capstone requirement:

  1. Take at least three credits of CSE 700 Independent Study.
  2. Obtain your advisor’s approval of a research artifact (a paper, software artifact, etc.).
  3. Present the research artifact in a public venue (typically at CSE Demo Day).

Elective Requirements

Complete any three approved elective courses, at least one of which must be offered by CSE.