Research

Intent estimator design for non-cooperative objects using Machine Learning and Inverse Reinforcement Learning

Planning algorithm design based on Machine Learning, Inverse Reinforcement Learning, and Deep Neural Networks

2D and 3D tracker design for the vision detection system based on Machine Learning

Sensor fusion algorithm design for ADS-B signals and vision detects

Deep Reinforcement Learning: Two-time Scale Actor-Critic based on Stochastic Approximation (projects: multi-actuator control designs for a self-driving car)

Deep Learning: Graph Neural Networks (projects: a vision based trailer sway estimator using deep learning and dynamic models)

Nonlinear Controls: Multi-Time-Scale Approaches, High-Gain Observer Design, On-line Optimizations, etc;

Stability Analysis for Stochastic Systems Using Stochastic Approximations

Machine Learning: Gaussian Process (estimations, probabilistic behavior planning, etc), Deep Neural Networks, Reinforcement Learning, etc 

Control Design with Cognitive Architecture: Graph Neural Networks and Episodic Memory

Dynamics: Under-actuated Mechanical Systems - Vehicle Dynamics (Chassis, Wheels controls - Traction Control System), Helicopters, Quadrotors, Robotic Boats, and a Powered Prosthetic Leg, etc.