I am currently an Assistant Professor at the University of Tulsa (Sep. 2024-present), where my research focuses on privacy-preserving and resilient optimization and estimation in adversarial networked cyber-physical systems. During my postdoctoral tenure at UC San Diego (2022-2024), I worked with Professor Sonia Martinez on these topics, particularly in the context of autonomous systems and robotics. In my Ph.D. (2018-2021) at Arizona State University, I collaborated with Prof. Sze Zheng Yong, focusing on guaranteed reachability analysis, state estimation of uncertain nonlinear systems, and resilient estimation in cyber-physical systems, particularly when facing uncertainty and malicious agents. My Ph.D. thesis, "Set-Valued Methods for Reachability Analysis and Estimation of Nonlinear Dynamical Systems", was awarded the prestigious 2021 ASU Dean's Dissertation Award.

My long-term research aims to leverage control theory, game theory, and decision science tools to develop distributed, robust, safe, and private algorithms for multi-modal and switched cyber-physical robotic systems. These innovations have broad applications, including enhancing the safety and security of autonomous vehicles, improving the resilience of smart grids against cyber threats, and optimizing energy-efficient operations in robotics for industrial automation and smart manufacturing. My work is also applicable to healthcare systems, where robust control and privacy-preserving algorithms can ensure safe and reliable medical device operation, even under adversarial conditions. If you are interested in my research or have questions, feel free to contact me at mohammad-khajenejad@utulsa.edu.