Electrical and Computer Engineering - Master of Engineering, Master of Science

For information, contact:

Director of Graduate Programs
Department of Electrical and Computer Engineering
260 Garland Hall, 513-529-0740
ECEdept@MiamiOH.edu
http://MiamiOH.edu/cec/academics/departments/ece/academics/graduate-studies/index.html

Electrical and Computer Engineering - Master of Engineering

The Master of Engineering (M. Eng.) in Electrical and Computer Engineering offers a course-intensive program with a culminating experience (internship, industrial practicum, or a non-thesis project). The program's mission is to prepare graduates with the versatile skills and mindset to meet the needs of a demanding and dynamic career in electrical/electronic, computer, and robotics industries. Students have the opportunity to gain experience in areas including artificial intelligence, machine learning, communications and networking, computer engineering, robotics and control, electromagnetics, power conversion, radars, signal processing, and others.

Program Requirements

(30 semester hours required)

Students design a program of study in consultation with a faculty advisor.

Note: Applicants must have completed an undergraduate degree to enroll in this program, and no BS/MS double counting of courses is allowed.

Culminating Experience 13-6
ECE 640
Internship
ECE 704
Non-Thesis Project
ECE 711
Industrial Practicum
Electrical and Computer Engineering Courses 215
Select from the following:
ECE 511
Sensors and Data Fusion with Robotics Applications
ECE 514
Design and Modeling of Robotic Systems
ECE 525
Digital Signal Processing
ECE 526
Biomedical Signal Analysis and Machine Learning
ECE 527
Radar Signal Processing
ECE 529
Digital Image Processing
ECE 530
Electromagnetics in Wireless Sensing and Communications
ECE 536
Control of Dynamic Systems
ECE 553
Communication Systems
ECE 561
Network Performance Analysis
ECE 570
Special Topics
ECE 587
Computer Aided Design Tools for Computer Engineering
ECE 591
Power Systems Engineering
ECE 593
Power Electronics
ECE 597
Electric Vehicle Technology
ECE 601
State Variables for Engineers
ECE 661
Advanced Optical Network Architectures
Elective Courses
Select 12 hours from unused ECE courses (above) or elective courses (below).12
Total Credit Hours30-33
1

Students must register for at least 3 credit hours of ECE 640, ECE 704, or ECE 711 for their culminating experience. The student will write a summary report and make a formal presentation, which should be evaluated and approved by a committee of at least two (2) members with Miami University graduate-level A or B standing.

2

Students design a program of study in consultation with their faculty advisor. Students are required to complete a minimum of 15 ECE credit hours but may take up to 27 credit hours to fulfill the requirements for the degree.

Elective Courses

While not required, students may select up to 12 credit hours in related disciplines.  In addition, students may petition the ECE Graduate Committee to approve courses outside of the list below.

CPB 612Engineering Analysis3
CSE 532Machine Learning3
CSE 543High Performance Computing & Parallel Programming3
CSE 556Bioinformatic Principles3
CSE 565Comparative Programming Languages3
CSE 573Automata, Formal Languages, and Computability3
CSE 584Algorithms II3
CSE 586Introduction to Artificial Intelligence3
CSE 588Image Processing & Computer Vision3
CSE 616Simulation of Physical Systems3
CSE 617Advanced Networks3
MME 595Introduction to Applied Nonlinear Dynamics3
MME 612Engineering Analysis3
MTH 525Number Theory3
MTH 532Optimization3
MTH 537Game Theory and Related Topics3
MTH 538Theory and Applications of Graphs3
MTH 551Introduction to Complex Variables4
MTH 553Numerical Analysis3
MTH 591Introduction to Topology3
MTH 632Advanced Optimization3
MTH 638Advanced Graph Theory3
MTH 641Functions of a Real Variable4
MTH 651Functions of a Complex Variable4
PHY 541Optics and Laser Physics4
PHY 561Electromagnetic Theory4
PHY 691Modern Quantum Physics4
PHY 692Modern Quantum Physics4
STA 527Introduction to Bayesian Statistics3
STA 562Inferential Statistics3
STA 563Regression Analysis4
STA 567Statistical Learning3
STA 583Analysis of Forecasting Systems3

Electrical and Computer Engineering - Master of Science 

Introduction

The Master of Science in Electrical and Computer Engineering is designed to graduate electrical and computer engineers who are well-qualified in advanced electrical and computer engineering technologies. This unique professional education prepares students for future interdisciplinary engineering practice that requires engineers to master both electrical/computer engineering and another discipline of choice. The degree includes electrical/computer engineering and elective courses in other disciplines. Students will conduct a research project with an electrical/computer engineering professor. 

Requirements include courses in electrical/computer engineering, elective courses, and a research-based thesis. The students work with a faculty adviser on a research problem of mutual interest.

Admission and Application Requirements

New students are generally admitted to begin in the fall semester. Entry into the program requires completion of a bachelor's degree in electrical or computer engineering, or a closely related field.

Prospective students will be ranked and considered for admission based on the following information:

  1. Requirements of the Graduate School, including: undergraduate transcripts, and TOEFL scores (if required)

  2. GRE scores (waived for Miami graduates)

  3. Three letters of recommendation

  4. The applicant's essay describing the purpose of his/her study.

Combined Bachelor/Master's Program

Undergraduate Miami University students may apply to participate in the combined bachelors/master’s program. This program allows you to pursue a master’s degree in an accelerated manner while completing your bachelor’s degree. It is a great opportunity to deepen your knowledge and research skills. Please contact the Department of Electrical and Computer Engineering for more information.

Program Requirements

The degree requires electrical and computer engineering courses, elective courses, and a thesis or research project. 

The curriculum requires completion of a minimum of 32 credit hours of graduate study and any additional hours needed to satisfy prerequisites. The distribution of hours is summarized as follows:

Electrical and Computer Engineering courses9-15
Elective courses3-9
ECE 610Graduate Seminars2
ECE 700Research for Master's Thesis12
Total Credit Hours32

Elective Courses

Students may enter the program with courses that cover some of the material in related disciplines; however, they must complete 3-9 credit hours of elective courses selected in consultation with their faculty adviser.

CPB/MME 612Engineering Analysis3
CSE 532Machine Learning3
CSE 543High Performance Computing & Parallel Programming 23
CSE 556Bioinformatic Principles 23
CSE 565Comparative Programming Languages3
CSE 573Automata, Formal Languages, and Computability 23
CSE 584Algorithms II 23
CSE 586Introduction to Artificial Intelligence 23
CSE 588Image Processing & Computer Vision3
CSE 616Simulation of Physical Systems3
CSE 617Advanced Networks3
CSE 627Advanced Machine Learning3
CSE 664Advanced Algorithms3
CSE 667Cryptography3
MME 595Introduction to Applied Nonlinear Dynamics 23
MME 612Engineering Analysis3
MTH 525Number Theory 23
MTH 532Optimization 23
MTH 537Game Theory and Related Topics 23
MTH 538Theory and Applications of Graphs 23
MTH 551Introduction to Complex Variables 24
MTH 553Numerical Analysis 23
MTH 591Introduction to Topology 23
MTH 632Advanced Optimization3
MTH 638Advanced Graph Theory3
MTH 641Functions of a Real Variable4
MTH 651Functions of a Complex Variable4
PHY 541Optics and Laser Physics 24
PHY 561Electromagnetic Theory 24
PHY 671Electromagnetism4
PHY 691Modern Quantum Physics4
PHY 692Modern Quantum Physics4
STA 527Introduction to Bayesian Statistics 23
STA 562Inferential Statistics 23
STA 563Regression Analysis 24
STA 567Statistical Learning 23
STA 583Analysis of Forecasting Systems 23

Electrical and Computer Engineering Courses

Students design a program of study in consultation with their faculty advisor. Courses are selected from the following:

ECE 511Sensors and Data Fusion with Robotics Applications3
ECE 514Design and Modeling of Robotic Systems3
ECE 525Digital Signal Processing 23
ECE 526Biomedical Signal Analysis and Machine Learning 23
ECE 527Radar Signal Processing 23
ECE 529Digital Image Processing 23
ECE 530Electromagnetics in Wireless Sensing and Communications 23
ECE 536Control of Dynamic Systems 23
ECE 553Communication Systems 23
ECE 561Network Performance Analysis 23
ECE 570Special Topics 23
ECE 587Computer Aided Design Tools for Computer Engineering 23
ECE 591Power Systems Engineering 23
ECE 593Power Electronics 23
ECE 597Electric Vehicle Technology 23
ECE 601State Variables for Engineers3
ECE 661Advanced Optical Network Architectures3
ECE 670Advanced Topics in Electrical and Computer Engineering 11-3
1

Maximum 6

2

Students who have taken the 400-level of this course or its equivalent must substitute another course.

Graduate Seminar Course

ECE 610Graduate Seminars2

Thesis and Project Research Courses

ECE 700Research for Master's Thesis12