Engineering Science MS: Robotics Focus

The Engineering Science MS with a course focus in Robotics is an interdisciplinary program that will train students in robotics, autonomy and automation, leading to employment opportunities in robotics, autonomous vehicles and advanced manufacturing industries among others, or to opportunities for continuing education at the Doctoral level in related fields.

Areas of training in our courses include dynamics and controls, robotic algorithms for perception and planning, computer vision, artificial intelligence (AI) and machine learning, design of electromechanical systems, automation platforms, and human-robot interaction.

Core Courses

CSE 568LEC - Robotics Algorithms Credits: 3
CSE 574LEC - Intro Machine Learning Credits: 3
MAE 593LEC - Robotics I Credits: 3
EAS 502LEC - Introduction to Probability Theory for Data Science Credits: 3
MAE 543LR - Continuous Control System Credits: 3
or
EAS 596LEC - Special Topics Credits: 3
* EAS 596 Course Topic: Special Topics- Cntrl Robotics Systems

Electives & Culminating Experience

Electives

Number of elective credits may vary depending on choice made to complete the culminating experience. Be sure to complete enough elective credit to reach 30 minimum total credit hours.

Dynamics and Controls
MAE 525LEC - Space Dyn & Cntrl Credits: 3
MAE 544LAB - Digital Control Systems Credits: 3
MAE 554LEC - Road Vehicle Dynamics Credits: 3
MAE 562LR - Analytical Dynamics Credits: 3
MAE 566LEC - System Identification Credits: 3
MAE 571LEC - Systems Analysis Credits: 3
MAE 670LEC - Nonlinear Control Credits: 3
MAE 672LEC - Optimal Control Systems Credits: 3
EE 519LEC - Industrial Control Systems Credits: 3
Algorithms, Systems and Design
CSE 531LEC - Algorithms Anal & Dsgn 1 Credits: 3
CSE 668LEC - Advanced Robotics Credits: 3
MAE 550LEC - Optimizat in Engrg Design Credits: 3
MAE 576LEC - Mechatronics Credits: 3
MAE 584LEC - Nano/Microtechnologies for (bio)MEMS Credits: 3
MAE 594LEC - Robotics II: Collaborative Robotics Credits: 3
EE 531LEC - Prob & Stoc Procs for Eng Credits: 3
EE 536LLB - Antennas and Propagation Credits: 3
IE 550LEC - Intro to Operations Research Credits: 3
IE 670LEC - Topics in Operations Rsch Credits: 3
Robot Perception
CSE 510LEC - Special Topics Credits: 1 - 3
CSE 573LEC - Comp Vision & Image Proc Credits: 3
CSE 666LEC - Biometrics Image Analysis Credits: 3
CSE 702SEM - Seminars Credits: 1 - 3
CSE 707SEM - Seminars Credits: 1 - 3
CSE 711SEM - Seminars Credits: 1 - 3
AI and Robot Learning
CSE 546LEC - Reinforcement Learning Credits: 3
CSE 555LEC - Intro Pattern Recognition Credits: 3
CSE 674LEC - Advanced Machine Learning Credits: 3
CSE 676LEC - Deep Learning Credits: 3
CSE 712SEM - Seminars Credits: 1 - 3
MAE 600LEC - Advanced Topics Credits: 3
Advanced Manufacturing
MAE 564LLB - Manufacturing Automation Credits: 3
IE 506LEC - Computer-Integrated Manuf Credits: 3
Human-Robot Interaction
MAE 502LEC - Special Topics Credits: 3
EE 526LEC - Wearable and Implantable Sensors Credits: 3
IE 530LEC - Intro to Human Factors Credits: 3
IE 538LEC - Human Factors Laboratory Credits: 3
IE 535LEC - Human Cent Design for Interact Credits: 3

Culminating Experience: Exam, Project or Thesis

EAS 561TUT - Robotics Project Credits: 1 - 3
EAS 562TUT - Robotics MS Thesis Guidance Credits: 1 - 6

Total Credit Hours: 30

3.0 Degree GPA required

Program Learning Outcomes (PLOs)

1) Ability to demonstrate domain expertise with engineering methods and tools

2) Ability to develop relevant programming abilities

3) Ability to use basic engineering concepts flexibly in a variety of contexts.

4) Ability to apply domain-specific concepts and methods to solve problems in real-world contexts and will communicate these solutions effectively

5) Demonstrate an ability to conduct professional practice

SED Statement

This program is officially registered with the New York State Education Department (SED).