Professional M.S. Degrees in Robotics, Autonomy and IoT
The Professional M.S. Degree in Autonomy focuses on the area of analysis, control and design of autonomous systems spanning a variety of application domains. The courses in this new major will establish fundamental theories and tools for modeling, analyzing and developing algorithms to achieve autonomy of both individual systems and a network of interconnected systems. It spans core topics such as control theories, machine learning, artificial intelligence, networks, as well as advanced courses in emerging topics.
The Professional M.S. Degree in IoT focuses on the area of analysis and design of internet-of-things such as a system of interrelated computer devices, mechanical and digital machines, sensors and so on that connect and exchange data over the internet or other communication networks. This area spans a variety of application domains. The courses in this major will establish fundamental theories and tools in computing, sensors, embedded systems, chip design, wireless communications.
The new Engineering Major in Robotics focuses on the area of analysis, control and design of robots spanning a variety of application domains. The courses in this new major will establish fundamental theories and tools for modeling, analyzing and developing techniques in robotics. It spans core topics such as control theories, machine learning, artificial intelligence, networks, as well as advanced courses in emerging topics such as robotics, manipulators, and human-robot teaming etc.
Student Clubs
Autonomous Robotics Club of Purdue
Faculty Mentors: Yu She (2023- ), Shaoshuai Mou (2019-2022)
The Autonomous Robotics Club of Purdue was created to grow the skills and abilities of its members through design projects centered around advanced autonomous robotics systems. It provides hands-on, real world experience to interdisciplinary teams using industry standard tools and practices.
Autonomous Motorsports Purdue
Faculty Mentor: Samuel Labi
The AMP student club was founded with a vision of building a strong research program for autonomous racing at Purdue. The team competes in the Indy Autonomous Challenge (https://www.indyautonomouschallenge.com/), with the goal of designing and optimizing algorithms for high speed (average 100 mph) autonomous racing.
Purdue Aerial Robotics Team
Faculty Advisor: Shreyas Sundaram
The Purdue Aerial Robotics Team mission is to create an Unmanned Aerial System (UAS) to compete in the Association for Unmanned Vehicle Systems International Student Unmanned Air Systems (AUVSI SUAS) Competition. This competition takes place in Webster Field, Maryland every June.
Boiler Robotics
Faculty Advisor: Sanjay Rebello
The Boiler Robotics Club competes in the University Rover Challenge, hosted by the Mars Society. We are building a mars rover that needs to accomplish a wide variety of tasks such as navigating autonomously, interacting with equipment, and detecting the presence of life in soil. We incorporate aspects from all areas of engineering, science, and business to achieve our goals. We strive to teach our members the skills they need to succeed in the club and in their professional career.
ICON Control Reading Group
Student Organizers: Ayush Rai, Hyunsang Park
The purpose of this control reading group is to enhance our learning by leveraging the outstanding control community at Purdue. We initiated our first reading group in Summer 2024 with a small number of members. Our goal is to meet once a week (in-person) to discuss new articles, book chapters, and research developments in control and related areas. The list of topics, papers, and facilitators is determined before the semester begins. During each meeting, we have a focused discussion of the selected paper/topics after a brief presentation. We do require attendees to read the paper before the meeting.
Graduate Courses in Control, Optimization, and Networks
Control and Systems
AAE 564: Systems Analysis and Synthesis
AAE 567: Introduction to Applied Stochastic Processes
AAE 568: Applied Optimal Control and Estimation
AAE 590: Multi-Agent Systems and Control
AAE 590: Aerospace Eng. Probability and Estimation Theory
AAE 668/ECE 695: Hybrid Systems: Theory and Applications
ECET 544 Real-Time and Embedded Systems
ECE 580: Optimization Methods for Systems and Control
ECE 602: Lumped System Theory
ECE 675: Introduction to Analysis of Non-Linear Systems
ECE 680: Modern Automatic Control
ME 575: Theory and Design of Control Systems
ME 576: Computer Control of Manufacturing Processes
ME 578: Digital Control
ME 580: Nonlinear Engineered Systems
ME 584: System Identification
ME 675: Multivariable Control System Designs
ME 677: Nonlinear Feedback Controller Design
ME 689: Adaptive Control
Optimization
AAE 561/IE 561: Introduction to Convex Optimization
ChE 597: Computational Optimization
ECE 647:Convex and Stochastic Optimization and Application
IE 535: Linear Programming
IE 537: Discrete Optimization Models and Algorithms
IE 538: Nonlinear Optimization Algorithms and Models
IE 590: Optimization for Big Data
IE 630: Multiple Objective Optimization
IE 633: Dynamic Programming
IE 634: Integer Programming
IE 635: Theoretical Foundations of Optimization
IE 639: Combinatorial Optimization
IE 646: Advanced Decision Theory
ECE 695: Optimization for Deep Learning
IE 690: Multi-Agent Optimization
IE 690: Advanced Queuing Theory
IE 690: Optimization, Game Theory, and Uncertainty
Networks
ECE 547: Introduction to Computer Communication Networks
ECE 600022: Wireless Communication Networks
ECE 695: Structure and Dynamics of Large-Scale Networks
ECE 695: Epidemic Processes Over Networks
IE 590: Stochastic Networks
IE 690: Stochastic Network Analysis
AI and Machine Learning
CE 597: Machine Learning and Artificial Intelligence for Autonomous Vehicle Operations
CS 578: Statistical Machine Learning
CS 590: Artificial Intelligence Meets Sustainability
CS 590: Reinforcement Learning
CS 590: AI Artificial Intelligence
ECE 570 Artificial Intelligence
ECE 570 Artificial Intelligence
ECE 595: Introduction to Deep Learning
ECE 695: Optimization for Deep Learning
ME 697Y: Intelligent Systems: Modeling, Optimization and Control
Data Science
IE 590: Optimization for Big Data
IE 690: Mathematics of Data Science
Robotics and Intelligent Swarms
AAE 590: Multi-Agent Systems and Control
ECE 569: Introduction to Robotic Systems
ME 572: Analysis and Design of Robotic Manipulators
IE 574: Industrial Robotics and Flexible Assembly
MFET 642 - Programming Robotics and Cyber-Physical Systems with the Robotics Commons
IE 690: Multi-Agent Optimization
Transportation, Infrastructures and Manufacturing
CE 514: Building Controls
CE 597: Transportation Infrastructure in the Era of Next-Generation Transportation Systems
CE 597: Data Science for Smart Cities
CE 597: Algorithms in Transportation
CE 597: The Science and Business of Logistics Systems
ECE 532: Computational Methods for Power System Analysis
IE 579: Design and Control of Production and Manufacturing Systems
IE 674: Computer and Communication Methods for Production Control
ME 597:Industrial IoT Implementation for Smart Manufacturing