Mohammad Khosravi
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Assisstant Professor Delft Center for Systems and Control
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Research
My primary interest lies in the theoretical and practical aspects of learning and control for various types of linear and nonlinear dynamical systems. I focus on data-driven and learning-based methods for modeling, optimization, model reduction, and control of dynamical systems, with applications in thermodynamic systems, energy, buildings, industry, and power plants.
Selected Publications
Khosravi, M., “Representer Theorem for Learning Koopman Operators”, IEEE Transactions on Automatic Control, 2023. [Link]
Khosravi, M., and Smith R.S., “The Existence and Uniqueness of Solutions for Kernel-Based System Identification”, Automatica, 2023. [Link]
Khosravi, M., and Smith R.S., “Kernel-Based Identification with Frequency Domain Side-Information”, Automatica, 2023. [Link]
Khosravi, M., and Smith, R.S., “Convex Nonparametric Formulation for Identification of Gradient Flows”, IEEE Control Systems Letters, 2021. [Link]
Khosravi, M., and Smith, R.S., “Nonlinear System Identification with Prior Knowledge on the Region of Attraction”, IEEE Control Systems Letters, 2021. [Link]
Khosravi, M., and Smith, R.S., “Kernel-based Impulse Response Identification with Side-Information on Steady-State Gain”, IEEE Transactions on Automatic Control, 2023. [Link]
Recent News
Our paper titled “Regularized Identification with Internal Positivity Side-Information” is accepted to be published in SIAM Journal on Control and Optimization.
Diyou has won the IEEE Student Travel Award to attand IEEE CCTA 2024 conference. Congrats!
Our paper titled “System Identification for Linear Dynamics with Bilinear Observation Models: An Expectation–Maximization Approach,” co-authored by my PhD student Diyou, has been accepted for presentation at the CDC 2024 conference.
Our paper titled “Mitigating short-sightedness of MPC for district heating networks using dual dynamic programming,” co-authored by our PhD student Max, has been accepted for presentation at the CDC 2024 conference.
Our paper titled “Learning Stable Evolutionary PDE Dynamics: A Scalable System Identification Approach,” co-authored by my PhD student Diyou, has been accepted for presentation at the IEEE CCTA 2024 conference.
Teaching
Statistical Signal Processing (SC42150)