Engineering Sciences MS: Focus on Robotics

Small robot on floor.
Students working on a robot in lab.
Robot moving a block on a conveyor belt in automation lab.

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Program Director

Vojislav Kalanovic
1006 Furnas Hall

About the Program

The Engineering Science- MS with a course focus in Robotics is an interdisciplinary program that will train students in robotics and expand knowledge in automation, leading to employment opportunities in automated manufacturing or continued education at the doctoral level.

Areas of training in our courses include robotic integration, motion control development, electromechanical system design, device/sensor development, automation platforms, and Artificial Intelligence (AI).

The job market demand for students with a background robotics and related fields is expected to continue to grow at an increased rate for companies in search of students trained in this area. Typically, a graduate degree is necessary for advancement in this field.

Entrance Requirements

We seek to admit students to our masters program with backgrounds or related coursework in electrical, mechanical, computer or any related engineering field, computer science, mathematics, physics or a related physical science field.

We are temporarily suspending the GRE requirement for admission to our Engineering Science MS (Robotics) Program for the Spring 2021 and Fall 2021 entry terms.

Degree Program Specifics

Students will take 10 courses for a total of 30 credits.  

Our flexible packaged curriculum enables students to focus on the core competencies related to that align with their own personal training goals that align to meet the needs of preparing them for their careers.

Course Requirements

Core Courses

  • CSE 568 Robotics Algorithms                                       
  • CSE 573 Computer Vision and Image Processing
  • CSE 574 Intro Machine Learning
  • MAE 507 Engineering Analysis 1 or MAE 567 Vibration and Shock 1
  • MAE 543 Continuous Control Systems or EAS 596 Robot Control Systems
  • MAE 593 Robotics I


Students will pick 2-3 electives; 2 electives if doing a 6-credit Master’s Thesis for the culminating experience and 3 courses if opting for the 3-credit Master’s Project.

  • CSE 546 Reinforcement Learning
  • CSE 668 Advanced Robotics
  • CSE 674 Advanced Machine Learning
  • CSE 676: Deep Learning
  • IE 506 Computer Integrated Manufacturing
  • MAE 525 Space Dynamics & Control
  • MAE 544 Digital Control Systems
  • MAE 550 Optimization in Engineering Design
  • MAE 562 Analytical Dynamics
  • MAE 564 Manufacturing Automation
  • MAE 566 System Identification
  • MAE 567 Vibration and Shock 1
  • MAE 571 Linear System Analysis
  • MAE 576: Mechatronics
  • MAE 577 Computer-Aided Design Applications
  • MAE 584 Principles and Materials for Micro-Electro-Mechanical Systems (MEMS)
  • MAE 594 Robotics II
  • MAE 670 Nonlinear Control
  • MAE 672 Optimal Control Systems

Culminating Experience

Students will have the option to complete either a 6-credit master’s thesis or a 3-credit project. The project can be completed either through an internship or through supervision with a faculty member.