Biography
Damoon Soudbakhsh is an assistant professor in the Department of Mechanical Engineering at Temple University. His research interests are in the broad area of optimal modeling and control. He is working on advancing analytical tools and data-driven modeling techniques, with an emphasis on energy systems. He has industry experience in developing resilient and energy-efficient transportation systems. He earned his Ph.D. from The George Washington University, Washington DC, in Transportation Safety. He introduced several advanced human-in-the-loop control techniques for active safety vehicle systems, including a steering-control collision avoidance system and an intelligent speed adaptation system.
He was a member of the Active Adaptive Controls Laboratory at the Massachusetts Institute of Technology (MIT) for four years. As a research scientist at MIT, he introduced algorithms for the co-design of Cyber-Physical Systems with examples in a variety of applications from automotive to wide-area-control of power systems. In addition, he developed adaptive algorithms for fault detection and health monitoring of jet engine components.
Damoon Soudbakhsh is a recipient of the Khwarizmi Young Award and the Dwight Eisenhower Transportation Fellowship Award. He has authored two book chapters in the Handbook of Intelligent Vehicles and Lecture Notes in Control and Information Sciences. He is a member of energy storage and networks systems technical committees. Also, he served as the Programs Chair of the ASME-Boston section from 2015 to 2017.
Research Interests
- Data driven and Physics-informed Machine Learning of Energy Storage Systems Health monitoring of energy systems Autonomous and semi-autonomous systems Cyber-Physical Systems Linear and nonlinear control Optimization Intelligent transportation systems
Courses Taught
Number | Name | Level |
|---|---|---|
ENGR 2332 | Engineering Dynamics | Undergraduate |
ENGR 3001 | Engineering Economics | Undergraduate |
MEE 3422 | Modeling and Control of Electromechanical Systems | Undergraduate |
MEE 4414 | Optimization and Control of Mechanical Systems | Undergraduate |
MEE 4422 | Mechanical Vibrations | Undergraduate |
MEE 5414 | Optimization and Control of Mechanical Systems | Graduate |
Selected Publications
Recent
Ahmadzadeh, O., Wang, Y., & Soudbakhsh, D. (2024). A data-driven framework for learning governing equations of Li-ion batteries and co-estimating voltage and state-of-charge. Journal of Energy Storage, 84, 110743-110743. Elsevier BV. doi: 10.1016/j.est.2024.110743.
Lukyanenko, A. & Soudbakhsh, D. (2023). Probabilistic motion planning for non-Euclidean and multi-vehicle problems. Robotics and Autonomous Systems, 168, 104487-104487. Elsevier BV. doi: 10.1016/j.robot.2023.104487.
Rodriguez, R., Wang, Y., Ozanne, J., Morrow, J., Sumer, D., Filev, D., & Soudbakhsh, D. (2023). Adaptive Learning and Optimization of High-Speed Sailing Maneuvers for America's Cup. Journal of Dynamic Systems, Measurement, and Control, 145(2). ASME International. doi: 10.1115/1.4056107.
Derakhshan, M., Sahraei, E., & Soudbakhsh, D. (2022). Detecting mechanical indentation from the time constants of Li-ion batteries. Cell Reports Physical Science, 3(11), 101102-101102. Elsevier BV. doi: 10.1016/j.xcrp.2022.101102.
Rodriguez, R., Wang, Y., Ozanne, J., Sumer, D., Filev, D., & Soudbakhsh, D. (2022). Adaptive Takeoff Maneuver Optimization of a Sailing Boat for America’s Cup. Journal of Sailing Technology, 7(01), 88-103. The Society of Naval Architects and Marine Engineers. doi: 10.5957/jst/2022.7.4.88.
Derakhshan, M. & Soudbakhsh, D. (2022). Temperature-Dependent Time Constants of Li-ion Batteries. IEEE Control Systems Letters, 6, 2012-2017. Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/lcsys.2021.3138036.
Soudbakhsh, D., Gilaki, M., Lynch, W., Zhang, P., Choi, T., & Sahraei, E. (2020). Electrical response of mechanically damaged lithium-ion batteries. Energies, 13(17). doi: 10.3390/en13174284.
Soudbakhsh, D., Annaswamy, A., & Voit, H. (2019). Adaptation in network control systems with hierarchical scheduling. IET Control Theory and Applications, 13(17), 2775-2782. doi: 10.1049/iet-cta.2018.6121.