I work on the theory and applications of dynamic optimization and reinforcement learning for world models, robotics, and control.
Presented our research on perturbation theory of dynamic programs at McGill University
New course ECE 6750 Linear Systems Theory (Spring 2026) — video lectures are on YouTube.
Two papers appeared in the IEEE Open Journal of Control Systems — on risk-sensitive robustness and dynamic watermarking for MDPs.
Taught ECE 7202 Reinforcement Learning (Autumn 2025); full lecture series available online.
“Probabilistic contraction analysis of iterated random operators” published in IEEE Transactions on Automatic Control.
I work on the theory and applications of dynamic optimization and reinforcement learning for world models, robotics, and control.
IEEE Open Journal of Control Systems, vol. 4, pp. 1–13 (2025)
@article{shao2025robustness,
title={Robustness to Modeling Errors in Risk-Sensitive Markov Decision Problems with Markov Risk Measures},
author={Shao, Shiping and Gupta, Abhishek},
journal={IEEE Open Journal of Control Systems},
year={2025},
volume = {4},
pages = {1--13},
publisher={IEEE}
}
IEEE Transactions on Automatic Control, vol. 69, no. 9, pp. 5947–5962 (2024)
@article{gupta2024probabilistic,
title={Probabilistic contraction analysis of iterated random operators},
author={Gupta, Abhishek and Jain, Rahul and Glynn, Peter},
journal={IEEE Transactions on Automatic Control},
volume={69},
number={9},
pages={5947--5962},
year={2024},
publisher={IEEE}
}
IEEE Open Journal of Control Systems, vol. 4, pp. 41–52 (2025)
@article{tang2025dynamic,
title={Dynamic Watermarking Algorithm for Finite Markov Decision Processes},
author={Tang, Jiacheng and Song, Jiguo and Gupta, Abhishek},
journal={IEEE Open Journal of Control Systems},
year={2025},
volume = {4},
pages = {41--52},
publisher={IEEE}
}
IEEE Transactions on Vehicular Technology, vol. 73, no. 2, pp. 1713–1725 (2023)
@article{zhu2023deep,
title={A deep reinforcement learning framework for eco-driving in connected and automated hybrid electric vehicles},
author={Zhu, Zhaoxuan and Gupta, Shobhit and Gupta, Abhishek and Canova, Marcello},
journal={IEEE Transactions on Vehicular Technology},
volume={73},
number={2},
pages={1713--1725},
year={2023},
publisher={IEEE}
}
Abhishek Gupta is an Associate Professor in the Department of Electrical and Computer Engineering at The Ohio State University. He earned his Ph.D. in Aerospace Engineering (2014), M.S. in Applied Mathematics (2012), and M.S. in Aerospace Engineering (2011) from the University of Illinois at Urbana-Champaign (UIUC), following his undergraduate degree in Aerospace Engineering from the Indian Institute of Technology Bombay (2005-09). His scholarly work spans the frontiers of artificial intelligence, game theory, and dynamic optimization, uniting deep theoretical insight with high-impact applied innovation. He is a co-author on three patent applications at OSU, two of which have been successfully commercialized. In recognition of his foundational contributions to stochastic control, he received the Lumley Research Award in 2019 from the College of Engineering at The Ohio State University.
A two-sided platform where businesses run loyalty programs and customers track their loyalty points. This product is deprecated and the business is shut down.