Mahendra Singh Tomar
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PostDoctoral Associate |
Bio and Research
Mahendra Singh Tomar is a PostDoc at the Department of Computer Science, University of Colorado Boulder since May 2021. He received his PhD degree from Department of Computer Science Ludwig Maximilian University Munich; B.Tech. degree (Electrical Engineering) from Indian Institute of Technology (ISM) Dhanbad, India; and M.Tech. degree (Electrical Engineering) from Indian Institute of Technology Roorkee, India. During masters, he was at Technical University of Munich for 6 months, supported by DAAD scholarship, to work on his thesis titled “Experimental Evaluation of Methods of Reachable Set Computation in Context of Symbolic Controller Synthesis”. His current research focuses on control under data-rate constraints. PhD thesis: Invariance feedback entropy of uncertain nonlinear control systems.
Publications
Mahendra Singh Tomar, and M. Zamani, “Modular computation of restoration entropy for networks of systems: a dissipativity approach” IEEE Control Systems Letters, vol.6,pp.3289-3294, 2022
Mahendra Singh Tomar, and M. Zamani, “On a notion of entropy for reachability properties” American Control Conference (ACC),pp.781-786, 2022
Mahendra Singh Tomar, C. Kawan, and M. Zamani, “Numerical over-approximation of invariance entropy via finite abstractions” Systems & Control Letters, vol.170,pp.105395,2022
Mahendra Singh Tomar, and M. Zamani, “Compositional quantification of invariance feedback entropy for networks of uncertain control systems” IEEE Control Systems Letters, 4(4),pp.827-832, October 2020
Mahendra Singh Tomar, M. Rungger, and M. Zamani, “Invariance feedback entropy of uncertain control systems” IEEE Transactions on Automatic Control, doi: 10.1109/TAC.2020.3038702
Immler, Fabian, Matthias Althoff, Xin Chen, Chuchu Fan, Goran Frehse, Niklas Kochdumper, Yangge Li, Sayan Mitra, Mahendra Singh Tomar, and Majid Zamani. “ARCH-COMP18 Category Report: Continuous and Hybrid Systems with Nonlinear Dynamics.” In Proc. of the 5th International Workshop on Applied Verification for Continuous and Hybrid Systems. 2018.
Pramod, C. P., Mahendra Singh Tomar, and G. N. Pillai. “A Modified Extreme Learning ANFIS for Higher Dimensional Regression Problems.” Computational Intelligence: Theories, Applications and Future Directions-Volume II. Springer, Singapore, 2019. 279-292.