Omkar Sudhir PatilControl • AI • Robotics

About Me

I’m a Postdoctoral Research Associate at the University of Florida with a PhD specializing in cutting-edge control systems, robotics, and deep learning-based methods. My work bridges advanced control theory, adaptive algorithms, and machine learning to design robust, real-time solutions for uncertain nonlinear systems and multi-agent environments. My research has led to breakthroughs in solving longstanding open problems in adaptive control and stability analysis, notably extending Lyapunov-based techniques to deep neural networks. I’ve developed innovative methods, ranging from Lyapunov-derived adaptive laws and safety-focused control barrier functions to physics-informed online learning algorithms, that have been implemented in real-world robotic platforms and validated through extensive experimentation. I’m always eager to connect with fellow researchers, industry professionals, and anyone interested in the intersection of control theory, robotics, AI, and machine learning. Let’s explore how innovative control strategies can transform robotics, automation, and beyond.

At a glance

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