Embedded Files
Teaching
Teaching
Lecturer
Lecturer
CAS ETH in Applied Automation Technology (2026 - ongoing)
Control Systems II and Optimal Control (Ashesi University, Ghana, 2025)
Head Teaching Assistant
Head Teaching Assistant
Linear System Theory (Fall 2020, Fall 2021, Fall 2022)
Teaching Assistant
Teaching Assistant
Distributed Systems & Control (ATIC) (Spring 2021, Spring 2022)
Signals and Systems II (Spring 2019, Spring 2020, Spring 2023)
Student Projects
Student Projects
I am always looking for talented students with interests in the area of optimal control, reinforcement learning, networked dynamical systems and related topics.
If you would like to apply, please send me an email with your CV and a transcript of records.
Example of past projects:
Example of past projects:
Data–Driven Feedback Dissipativity of Discrete–Time LTI Systems
Data–Driven Feedback Dissipativity of Discrete–Time LTI Systems
This project aims at understanding and advancing theories at the intersection between dissipativity theory and data-driven control for linear time-invariant (LTI) discrete-time systems.
Plug-and-play control of interconnected systems
Plug-and-play control of interconnected systems
Varying-topology networks have attracted the attention of the control systems community due to their broad range of applications, such as microgrids and power networks. In this project we are interested in developing plug-and-play controllers which ensure stability and feasibility for such complex networks.
Dynamic programming via the randomized mini-batch Gauss-Seidel operator
Dynamic programming via the randomized mini-batch Gauss-Seidel operator
The Bellman operator constitutes the foundation of dynamic programming algorithms. This project focuses on the study of a practical and theoretically sound extension of the Bellman operator, which we call randomized mini-batch Gauss-Seidel operator.
Data-driven optimal control via linear programming
Data-driven optimal control via linear programming
Learning how to optimally regulate a dynamical system from data is a fundamental problem in control theory. This project focuses on investigating new theory and methods about the so-called linear programming approach to approximate dynamic programming.
Page updated
Google Sites
Report abuse