Model-Free and Data-Driven Control and Optimization

Robotics, Machine Learning, Control Theory, Optimization, and Computer Vision

Systems and control, sensor networks, game theory, adversarial networks, cooperative robotics, and geometric mechanics

Controls and differential equations

Practical algorithms for NP-hard search and optimization problems in the decision, control, and design aspects of computational systems

Multifidelity and data-driven modeling, optimization, and control, uncertainty quantification, reliability-based design, and design under uncertainty in fluid flows

Nonlinear Control, Adaptive Systems, Delay Systems, Extremum Seeking 

Distributed motion coordination, distributed estimation, optimal control for robotic locomotion, motion planning for underactuated systems

Hybrid control, nonlinear control, optimization, adaptive systems, learning-based control

Energy systems, cyber-physical systems, machine learning for energy management

Reinforcement Learning for Robots; Computationally Efficient Robot Planning; Robot Manipulation in Dynamic Environments; Autonomous Robotic Surgery; Mechanical Design of Surgical Robots; Continuum and Snake-like Robots; Artificial Muscles

Theory and Applications of Optimization, Sampling, Online Learning, Game Theory, Trustworthy Machine Learning

Learning, Optimization, and Control of Network Systems, and their Applications to Autonomous Vehicles and Traffic Systems