Hemanth Manjunatha is an Assistant Professor at Oklahoma State University with a decade of experience bridging human–machine interaction, safe cyber-physical systems, deep learning, and reinforcement learning. His academic trajectory includes a PhD and MSc from the University at Buffalo and a postdoctoral fellowship at Georgia Tech, where he advanced research at the intersection of robotics and learning-based control. He has blended hands-on work in sustainable manufacturing and advanced robotics with theoretical contributions to safe RL and HRI, making systems that prioritize both performance and human trust. Based in Stillwater, Oklahoma, he brings a strong mechanical engineering foundation (B.E., 3.835/4.0) to data-driven robotics research and teaching. An understated piece of his profile: he smoothly moves between lab-scale robotic platforms and algorithmic development, translating experimental insights into safer real-world deployments.
10 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, Human robot interaction, Reinforcement Learning, Deep learning, Doctor of Philosophy - PhD, Human robot interaction, Reinforcement Learning, Deep learning at University at Buffalo
Bachelor of Engineering (B.E.), Mechanical Engineering, 3.835/4.0, Bachelor of Engineering (B.E.), Mechanical Engineering, 3.835/4.0 at The National Institute of Engineering
Contributions:5 PRs, 40 pushes, 4 branches in 4 years 1 month
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Hemanth Manjunatha - Assistant Professor at Oklahoma State University