Master of Science in Computer Engineering

The Master of Science in Computer Engineering degree program educates students to acquire a strong fundamental background in computer engineering and state-of-the-art knowledge and hardware and software skills applied for cutting edge areas such as embedded systems, networks and security, software and data engineering, and artificial intelligence. The program focus is on problem-solving skills development for real-world applications, with an emphasis on research experience. Our student-centric learning environment provides a variety of opportunities, accelerated graduate degrees, co-op opportunities and internships. 

Concentrations

  • Embedded Systems

  • Software and Data Engineering

  • Networks and Security

  • Artificial Intelligence

 

Program Objectives

The program prepares students to:

  • apply specialized knowledge in computer engineering at an advanced level.

  • perform independent research in the computer engineering field.

Program Outcomes

By the time of graduation, students will be able to:

  • apply knowledge of mathematics and physics to problem solving in computer engineering.

  • analyze computer systems using engineering principles and modeling approaches

  • design experiments and analyze results to determine process parameters, and to identify issues and methods for computer engineering measurements.

  • use mathematical, modeling, and engineering principles to design computer engineering processes

  • incorporate considerations such as feasibility, applicability, cost, legal/regulatory, societal impacts, etc. in designs.

  • use computer software for data analysis, reporting and presentations.

  • be capable of writing and presenting polished technical reports at a level expected of the engineering profession and be able to critically evaluate the technical literature and use it to obtain solutions to computer engineering problems.

  • work effectively in a team.

  • develop intellectual property.

  • recognize and achieve high levels of professionalism in work and understand ethical and moral systems in a social context.

Degree Requirements

The program is a 30-credit degree program. Students are required to complete:

  • 1 mathematical foundation course (3 credits)

  • 4 core courses (12 credits)

  • 3 concentration courses in a chosen concentration (9 credits)

  • 3 credits of project work (CPE 800) co-requisite with EE 820 (0 credit) and 3 credits elective course (Project Track), or 6-credit thesis (Thesis Track)

Students in the Master of Science program are required to complete:

  • Project Track: 3-credit project course (800 course) and a 3-credit elective course at the 500 or 600 level. Students who enroll in the 3-credit project course (800 course) are required to enroll in the 0-credit co-requisite research seminar course, EE 820. The 3-credit elective course can be any graduate level course at the 500 or 600 levels within the Department of Electrical and Computer Engineering. Elective courses that are taken outside of the department require approval by the student's faculty advisor.

OR

  • Thesis Track: 6-credit thesis course (900 course). Students need to take the first 3-credit thesis course (900 course) in their second to last semester and the second 3-credit thesis course (900 course) in their last semester.

Mathematical Foundation Courses

Students are required to select one mathematical foundation course from the list below: 

CPE 602Applied Discrete Mathematics

3

Or

EE 605Probability and Stochastic Processes I

3

Core Courses

Students are required to select four courses from the following list:

CPE 517Digital and Computer Systems Architecture

3

CPE 555Real-Time and Embedded Systems

3

CPE 593Applied Data Structures and Algorithms

3

CPE 690Introduction to VLSI Design

3

EE 608Applied Modeling and Optimization

3

Concentrations

Students are required to select three courses from one of the concentrations listed below:

Artificial Intelligence Concentration Course Options

Students who select the Artificial Intelligence concentration are required to select three concentration courses from the list below: 

AAI 551Engineering Programming: Python

3

AAI 672Applied Game Theory and Evolutionary Algorithms

3

AAI 627Data Acquisition, Modeling and Analysis: Big Data Analytics

3

AAI 628Data Acquisition, Modeling and Analysis: Deep Learning

3

AAI 646Pattern Recognition and Classification

3

AAI 695Applied Machine Learning

3

Embedded Systems Concentration Course Options

Students who select the Embedded Systems concentration are required to select three concentration courses from the list below: 

CPE 517Digital and Computer Systems Architecture

3

CPE 555Real-Time and Embedded Systems

3

CPE 556Computing Principles for Mobile and Embedded Systems

3

CPE 690Introduction to VLSI Design

3

EE 629Internet of Things

3

Networks and Security Concentration Course Options

Students who select the Network and Systems Security concentration are required to select three concentration courses from the list below: 

CPE 579Foundations of Cryptography

3

Or

CS 579Foundations of Cryptography

3

EE 584Wireless Systems Security

3

CPE 654Design and Analysis of Intelligent Network Systems

3

CPE 679Computer and Information Networks

3

CPE 691Information Systems Security

3

Software and Data Engineering Concentration Course Options

Students who select the Software and Data Engineering concentration are required to select three concentration courses from the list below: 

CPE 593Applied Data Structures and Algorithms

3

EE 551Engineering Programming: Python

3

EE 552Engineering Programming: Java

3

EE 553Engineering Programming: C++

3

EE 627Data Acquisition, Modeling and Analysis: Big Data Analytics

3

Or

AAI 627Data Acquisition, Modeling and Analysis: Big Data Analytics

3

EE 628Data Acquisition, Modeling and Analysis: Deep Learning

2

Or

AAI 628Data Acquisition, Modeling and Analysis: Deep Learning

3

EE 629Internet of Things

3

CPE 810Special Topics in Computer Engineering

3-6

Project or Thesis

Students in the Master of Science program are required to complete:

  • Project Track: 3 credit project course (800 course) and a 3 credit elective course at the 500 or 600 level. Students who enroll in the 3 credit project course (800 course) are required to enroll in the 0-credit co-requisite research seminar course, EE 820. The 3 credit elective course can be any graduate level course at the 500 or 600 levels within the Department of Electrical and Computer Engineering. Elective courses that are taken outside of the department require approval by the faculty advisor.

OR

  • Thesis Track: 6 credit thesis course (900 course). Students need to take the first 3 credit thesis course (900 course) in the third semester and the second 3 credit thesis course (900 course) in the fourth semester.