M.S. in Computer Engineering

Overview

The M.S. in Computer Engineering program brings students to the leading edge of computer engineering by solving real-life problems which then contributes to the advancement of local communities and of society as a whole. This program is designed to prepare students for career advancement, or for further studies at the doctoral level. It has two options, thesis and professional (non-thesis). It is a research-based program of study, requiring students to complete independent research that culminates in several projects, and, in one of the options, with a thesis project.

Unique to our program is the focus on optimization and stochastic models, taught by experienced faculty who have extensive expertise in convex optimization for design of VSLI circuits, application of semi-Markov models for optimization of wireless networks, and queueing theory for tele-traffic analysis. 

Designed With You in Mind

Either option includes a rigorous curriculum and allows students to concentrate their program in the following specialized areas: 

• Computer Architecture and Distributed Computing
• Advanced Computer Networks (including Cybersecurity)
• VLSI Circuit Design
• Robotics, Artificial Intelligence, and Machine Learning (including Computer Vision)

Students gain marketable skills that propel them to being leaders in computer-related industries:

• Ability to identify and solve complex technology problems in robotics, aerospace, business, medicine, military and other essential areas.
• Soft skills in complex problem-solving, communication and creative thinking. A computer engineer must communicate with end-users, managers and vendors to determine computing goals and system requirements, but also with other scientists to solve the complex computing problems that arise.
• Ability to apply and adapt theoretical principles to develop new computer software and/or hardware.
• Computer-related math skills, e.g., linear algebra, calculus, statistics, discrete mathematics, and optimization.
• Fluency in the main current programming languages, such as C/C++; must continue learning new languages as they emerge.
• Technical writing skills to document and publish their findings and designs.
• Ability to teach engineering and computer science across all levels of academia.
• Complex systems engineering
• Logic (circuit) design