Associate Professor – Electrical & Computer Engineering
Teaching
Teaching Experience
In-Person Courses
520.241: Intro to Mechatronics(Undergraduate Level, Johns Hopkins University)
Semesters: Spring 2023, 2024
Description: Introduction to the integration of mechanical, electronic, and software components for robotic and automated systems.
520.353: Control Systems (Undergraduate Level, Junior Year, Johns Hopkins University)
Semesters: Spring 2017, 2018, 2019, 2020, 2021, 2022
Description: Introduces classical and modern control methods, stability analysis, and feedback systems, emphasizing practical applications.
520.629: Networked Dynamical Systems (Graduate Level, Johns Hopkins University)
Semesters: Fall 2016, 2017, 2018, 2019
Description: Explores dynamics, control, and optimization in networked systems with applications to power grids, transportation, biology, and social networks..
520.637: Foundations of Reinforcement Learning (Graduate Level, Johns Hopkins University)
Semesters: Spring 2020, 2021, 2022, 2023, 2024, 2025
Description: Rigorous treatment of reinforcement learning, covering dynamic programming, temporal-difference methods, policy gradients, and deep Q-learning. Emphasis on theoretical foundations. Includes practical Python/Jupyter projects.
Online Courses
525.637: Foundations of Reinforcement Learning(Graduate Level, Engineering Professional Program, Johns Hopkins University)
Semesters: Fall 2021, 2022, 2023, 2024, 2025
Description: Online delivery of foundational reinforcement learning concepts with practical control and optimization applications.
Summer Schools and Workshops
Reinforcement Learning Summer School(Peking University, July 2025)
Topics: Value iteration, policy iteration, TD learning, exploration strategies, on-policy and off-policy methods, modern deep RL methods.