AI/ML-Enabled Control Systems

Safe Learning • Control Theory • Networked Control • Model Predictive Control • Robotics • Autonomous Systems • Process Control

Welcome to my research website. My research focuses on the integration of Artificial Intelligence and Machine Learning (including Reinforcement Learning, Bayesian Optimization, Gaussian Processes, and other data-driven methods) with optimization and control theory to develop AI/ML-enabled decision-making, estimation, and control algorithms for autonomous systems, Cyber-Physical Systems (CPSs), Guidance, Navigation and Control (GNC), robotics, and Advanced Process Control (APC).

Research Areas & Expertise

Control and Estimation Theory

Nonlinear Control, Optimal Control, Control Barrier Functions, Robust MPC, EKF/UKF/MHE, State Estimation-integrated MPC, Stochastic MPC, Data-Driven MPC, Koopman MPC, Belief-Space MPC, and Distributed MPC.

AI/ML and Optimization

Reinforcement Learning (RL), Safe RL, MPC-based RL, Multi-Agent RL, Bayesian Optimization and Active Learning, Stochastic Optimization, Uncertainty Quantification, Bayesian Inference, Gaussian Process, Deep Learning, and Distributed Learning.

Autonomous Systems

GNC, robotics, unmanned vehicles, cyber-physical systems, and process control.

About Me

I received my M.Sc. in Mechatronics Engineering from the University of Tabriz in 2012 and subsequently worked as an instrumentation and control engineer in the steel, power, and oil and gas industries, where I developed control, diagnostics, and monitoring systems for industrial automation. In 2018, I transitioned from industry back to academia, joining Gdańsk University of Technology (GUT) as a Research and Teaching Assistant before moving to the Norwegian University of Science and Technology (NTNU) in 2020 as a Research Fellow. I earned my first Ph.D. in Electrical Engineering (Engineering Cybernetics) from NTNU in 2023, focusing on the integration of Reinforcement Learning (RL) and Model Predictive Control (MPC). I then joined Clemson University, where I completed a second Ph.D. in Mechanical Engineering in 2025 and have since continued as a Postdoctoral Fellow. My research integrates artificial intelligence, machine learning, optimization, and control theory to develop AI/ML-enabled safety-critical control and decision-making algorithms for autonomous systems, cyber-physical systems, energy management, guidance, navigation and control (GNC), robotics, and advanced process control.

Hossein Esfahani