- Described a modular approach to approximate smallest feedback data rate for state estimation over finite bit rate channel. Utilized distributed optimization; MATLAB. Published in Journal: IEEE Control Systems Letters. Accepted in Conference on Decision and Control 2022.- Introduced a notion of reachability entropy to characterize smallest data rate sufficient enough to enforce reach-while-stay specification. Computational estimation via finite abstractions; used C++, Python and MATLAB. Presented in American Control Conference 2022.- Described for first time approaches to computationally estimate smallest data rate from sensor to controller to enforce set invariance. Utilized set-valued numerical analysis, graph-theoretic constructions, symbolic models; used C++, Python and MATLAB. Accepted in Journal: Systems and Control Letters. https://github.com/mahendrasinghtomar/Invariance_Entropy_upper_bounds

- Introduced a modular approach to estimate invariance feedback entropy for networks of interconnected uncertain control systems; reduces computational complexity. Published in Journal: IEEE Control Systems Letters. Presented in Conference on Decision and Control 2020.- Extended the notion of invariance entropy to uncertain control systems. Utilized mean-payoff games. Published in IEEE Transactions on Automatic Control