Research activities
I am passionate about Reinforcement Learning and Control theory. I would like to explore these two fields and find their connection.
Reinforcement Learning (RL) with Continuous State and Action Space
In this project, I develop RL techniques for dynamical systems with continuous state and action space. I consider dynamical uncertainty and I use robust and stochastic control theories along with adaptive dynamic programming approaches to develop RL algorithms for dynamics systems with uncertainty.
Multi-agent Systems
During my Ph.D., my research study focused on distributed control of linear heterogeneous multi-agent systems. More specifically, I obtained necessary and sufficient conditions for a group of linear heterogeneous agents to achieve a desired collective behavior like output regulation, $H_{\infty}$ output regulation, bipartite output regulation, multi-party output regulation and formation control. I also developed RL techniques for distributed control of multi-agent systems.
SLAM and Mobile Robot Navigation
I am also interested in Simultaneous Localization And Mapping (SLAM) in Dynamic Environment Using Grid Based Map. During my master's study, I worked on navigation of a nonholonomic mobile robot in dynamic environment. The primal task of the robot was to do SLAM in a dynamic environment and for this purpose, I proposed algorithms to distinguish between dynamic and static obstacles, and to re-do path planning.
Education
I received my bachelor and master's degrees from K. N. Toosi University of Technology, Tehran, Iran in 2009 and 2011. In 2013, I joined Nanyang Technological University (NTU) in Singapore as a Ph.D. Student and I received my Ph.D. degree with the "Best Thesis award" in 2017.
Ph.D., Electronic and Electrical Engineering
Nanyang Technological University (NTU), Singapore
Master Degree, Electrical Engineering, Control
K. N. Toosi University of Technology, Tehran, Iran
Bachelor Degree, Electrical Engineering, Control
K. N. Toosi University of Technology, Tehran, Iran
For more information about me, please visit;
Googlescholar
Linkedin
Research Gate
NEWS
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2021-Apr: The second day of Reinforcement Learning workshop is on 6 April. Try some of the simplest RL algorithms in your browsers now!
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2021-Mar: You can now go through our simple handout about Reinforcement Learning entitled "A Crash Course on RL" on Arxiv: short, easy to read and comprehensive!
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2021-Mar: The first day of Reinforcement Learning workshop is on 13 March.
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2021-Jan: I will have a workshop on RL for control at LiU, Linköping, Sweden in March. More details coming soon!
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2020-Nov: Checkout my Github page for a crash course on RL. Find out how to implement RL for problems with continuous and discrete action spaces
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2020-Sep: I received a CENIIT grant!
Reinforcement
https://doi.org/10.1109/TAC.2024.3385680
