PRABHAT KUMAR MISHRA

About

I am an Assistant Professor with the Department of Artificial Intelligence (DAI), Indian Institute of Technology Kharagpur (IITKgp), India, and currently working at the intersection of control and learning. I am developing algorithms for autonomous systems to make them smarter with the help of data and distribution. I use control theory to provide safety certificates, and to enhance explainability and trustworthiness of AI driven techniques.

I did PhD from the Indian Institute of Technology Bombay (IITB), India, on Stochastic Model Predictive Control (MPC) for Cyber Physical Systems. During my PhD, I received a Swiss Government Excellence Scholarship to study at the Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland, for one year. I learnt Gaussian process regression and implemented stochastic MPC on a quadcopter during my stay at EPFL.

Before joining IITKgp, I was a Postdoctoral Associate at the Massachusetts Institute of Technology (MIT), USA, and working on polynomial chaos theory for advanced manufacturing applications. Prior to that, I was a Postdoctoral Research Asssociate at the University of Illinois at Urbana Champaign (UIUC), USA, where we developed a couple of deep learning supported MPC algorithms and a constrained estimator for the agricultural robotics and aerospace applications.

Employment

• Indian Institute of Technology Kharagpur Assistant Professor
  2023 - Present
• Massachusetts Institute of Technology Post-doctoral Associate
  2023 - Present
• University of Illinois at Urbana-Champaign Post-Doctoral Research Associate
  2019 - 2023
• Indian Institute of Technology Bombay Research Associate
  2018 - 2019

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (14)

• Deep Model Predictive Control With Stability Guarantees
  IEEE Transactions on Automatic Control 2025 DOI: 10.1109/TAC.2025.3550072
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• Minimum variance constrained estimator
  Automatica 2022 DOI: 10.1016/j.automatica.2021.110106
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• Reference tracking stochastic model predictive control over unreliable channels and bounded control actions
  Automatica 2021 DOI: 10.1016/j.automatica.2021.109512
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• Centralized model predictive control with distributed adaptation
  Proceedings of the IEEE Conference on Decision and Control 2020 DOI: 10.1109/CDC42340.2020.9304097
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• Stochastic predictive control under intermittent observations and unreliable actions
  Automatica 2020 DOI: 10.1016/j.automatica.2020.109012
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• Sparse and constrained stochastic predictive control for networked systems
  Automatica 2018 DOI: 10.1016/j.automatica.2017.09.013
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• Stabilizing stochastic predictive control under bernoulli dropouts
  IEEE Transactions on Automatic Control 2018 DOI: 10.1109/TAC.2017.2765740
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• Output feedback stable stochastic predictive control with hard control constraints
  IEEE Control Systems Letters 2017 DOI: 10.1109/LCSYS.2017.2719606
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• Resource efficient stochastic predictive control under packet dropouts
  IET Control Theory and Applications 2017 DOI: 10.1049/iet-cta.2016.0879
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• Dropout feedback parametrized policies for stochastic predictive controller
  IFAC-PapersOnLine 2016 DOI: 10.1016/j.ifacol.2016.10.140
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