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Arunava Naha is an Assistant Professor at Linköping University, specializing in control theory and optimization. His research primarily focuses on policy gradient methods in control systems, particularly in the context of probabilistic constraints and optimal control. He has co-authored several significant publications, including studies on convergence flow-policy gradient learning and model-free optimal LQG control. His work often intersects with cyber-physical systems and networked control, addressing challenges such as deception attacks and watermarking techniques. Naha's contributions to the field are recognized through collaborations with peers and an increasing number of publications in renowned journals and conferences. His research interests extend to enhancing the robustness and efficiency of control mechanisms in complex systems, making significant strides in theoretical and applied aspects of control engineering.
Linköping University • Linköping, Sweden
Teaching and researching topics in control theory and optimization.
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