Electrical and Computer Engineering with Concentration in Computer Vision, Machine Learning, and Algorithms, MSECE

The master's degree program in electrical and computer engineering offers in-depth course work within the concentration-choice-related areas. The curriculum is integrated and intensive and is built on state-of-the-art research, taught by faculty who are experts in their areas.

Excluded Courses for All MSECE Concentrations

You cannot take excluded courses as part of your MSECE program. Please do not petition to take these courses, as any petition to take these courses will be automatically rejected. Courses from the following subject areas may not count toward any concentration within the MSECE program: CSYE, ENSY, EMGT, INFO, SBSY, TELE. Select CS courses are also excluded from all MSECE concentrations. Please see the program requirements tab and your college administrator for more information. 

Graduate Certificate Options

Students enrolled in a master's degree have the opportunity to also pursue one of the many engineering graduate certificate options in addition to or in combination with the MS degree. Students should consult their faculty advisor regarding these options.

Gordon Institute of Engineering Leadership

Master's Degree in Electrical and Computer Engineering with Concentration in Computer Vision, Machine Learning, and Algorithms with Graduate Certificate in Engineering Leadership  

Students may complete a Master of Science in Electrical and Computer Engineering with Concentration in Computer Vision, Machine Learning, and Algorithms in addition to earning a Graduate Certificate in Engineering Leadership. Students must apply and be admitted to the Gordon Engineering Leadership Program in order to pursue this option. The program requires fulfillment of the 16-semester-hour curriculum required to earn the Graduate Certificate in Engineering Leadership, which includes an industry-based challenge project with multiple mentors. The integrated 48-semester-hour degree and certificate will require 32 semester hours of advisor-approved computer vision, machine learning, and algorithms technical courses.

Engineering Leadership

Complete all courses and requirements listed below unless otherwise indicated.

Options

Complete one of the following options:

Course Work Option

Depth Courses
Complete 20 semester hours from the depth course list below.20
Breadth Courses
Complete 8 semester hours from the breadth course list below or other EECE courses chosen in consultation with a faculty advisor.8
Note: Depth courses cannot be taken for breadth.
Elective
Complete 4 semester hours of either depth or breadth courses.4

Thesis Option

Depth Courses
Complete 12 semester hours from the depth course list below.12
Breadth Courses
Complete 8 semester hours from the breadth course list below or other EECE courses chosen in consultation with a faculty advisor.8
Note: Depth courses cannot be taken for breadth.
Elective
Complete 4 additional semester hours from either depth or breadth courses. 4
Thesis
EECE 7990Thesis8

Course Lists

Depth Courses  

Mobile Robotics
Robotics Sensing and Navigation
Computer Vision
High-Performance Computing
Data Visualization
Introduction to Machine Learning and Pattern Recognition
Special Topics in Electrical and Computer Engineering (Parallel Processing for Data Analytics)
Autonomous Field Robotics
Applied Probability and Stochastic Processes
Fundamentals of Computer Engineering
Human Sensing and Recognition
Numerical Optimization Methods
Big Data and Sparsity in Control, Machine Learning, and Optimization
Computer Architecture
Combinatorial Optimization
Advanced Computer Vision
Advanced Machine Learning
Special Topics (Big Data and Sparsity in Control, Machine Learning and Signal Processing)
Special Problems in Electrical Engineering
Foundations of Artificial Intelligence
Information Retrieval
Data Mining Techniques
Advanced Algorithms
Graph Theory

Breadth Courses

Wireless Sensor Networks and the Internet of Things (Wireless Sensor Networks and the Internet of Things -- former special topics course)
Thin Film Technologies (Thin Film Technologies -- former special topics course)
Introduction to Multiferroics Materials and Systems
Assistive Robotics (Principles of Assistive Robotics)
Wireless Communication Systems
Classical Control Systems
Micro- and Nanofabrication
Digital Control Systems
Arithmetic and Circuit Design for Inexact Computing with Nanoscaled CMOS
Simulation and Performance Evaluation
Nanophotonics
Biomedical Optics
Design of Analog Integrated Circuits with Complementary Metal-Oxide-Semiconductor Technology
Biomedical Signal Processing
Digital Signal Processing
Electric Drives
and Lab for EECE 5680
Power Systems Analysis 1
Power Electronics
and Lab for EECE 5684
Electrical Machines
Analysis of Unbalanced Power Grids
Acoustics and Sensing
Special Topics in Electrical and Computer Engineering (Software Security )
Special Topics in Electrical and Computer Engineering (GNSS Signal Processing)
Special Topics in Electrical and Computer Engineering (Networks: Technology, Economics, Social Interactions)
Special Topics in Electrical and Computer Engineering (Introduction to Molecular Systems Biology Dynamic Modeling)
Special Topics in Electrical and Computer Engineering (Advanced Network Management)
Special Topics in Electrical and Computer Engineering (Principles of Assistive Robotics)
Optics for Engineers
Linear Systems Analysis
Solid State Devices
Electromagnetic Theory 1
Complex Variable Theory and Differential Equations
Nonlinear Control
System Identification and Adaptive Control
Optimal and Robust Control
Power Systems State Estimation
Modeling and Simulation of Power System Transients
Advanced Power Electronics (Advanced Power Electronics -- former special topics course)
Special Topics in Power Electronics
Analog Integrated Circuit Design
Integrated Circuits for Mixed Signals and Data Communication
Introduction to Microelectromechanical Systems (MEMS)
Microwave Circuit Design for Wireless Communication
Power Management Integrated Circuits (Power Management Integrated Circuits -- former special topics course)
Humanoid Robotics (Humanoid Robotics -- former special topics course)
Electromagnetic Theory 2
Computational Methods in Electromagnetics
Antennas and Radiation
Modern Imaging
Electronic Materials
Advanced Magnetic Materials—Magnetic Devices
Magnetic Materials—Fundamentals and Measurements
Modern Signal Processing
Two Dimensional Signal and Image Processing
Statistical and Adaptive Signal Processing
Digital Communications
Information Theory
Big Data and Sparsity in Control, Machine Learning, and Optimization
Probabilistic System Modeling and Analysis
VLSI Design
Mobile and Wireless Networking
High-Level Design of Hardware-Software Systems
Fundamentals of Computer Networks
Operating Systems: Interface and Implementation
Scalable and Sustainable System Design (Scalable and Sustainable System Design)
Computer Hardware Security
Special Topics (Compilers )
Special Topics (Advanced Computer Architecture)
Special Topics (Power System Constrained Optimization)
Preparing High-Stakes Written and Oral Materials
Sustainable Energy: Materials, Conversion, Storage, and Usage
Database Management Systems
Computer Systems
Software Vulnerabilities and Security
Compilers
Advanced Software Development
Network Security
Cryptography and Communications Security
Privacy, Security, and Usability

Excluded Courses for All MSECE Concentrations

 Please see your college administrator for more information.

Courses from the following subject areas may not count toward any concentration within the MSECE program:
CSYE, ENSY, EMGT, INFO, SBSY, TELE
The following CS courses may not count toward any concentration within the MSECE program:
Programming Design Paradigm
CS 5320
Pattern Recognition and Computer Vision
Computer/Human Interaction
Mobile Application Development
Web Development
Fundamentals of Computer Networking
Algorithms
Empirical Research Methods
Wireless Network

Program Credit/GPA Requirements

32 total semester hours required
Minimum 3.000 GPA required