About

Anirudh Vemula is a highly skilled roboticist with extensive experience in developing advanced robot motion planning algorithms for problems with complex constraints. Currently working as a PhD Research Intern at Apple, Anirudh has conceptualized a novel algorithmic solution that was deployed and tested in simulation and on a real hardware system. He has also worked with Martin Levihn and Chris Clark in Special Projects Group at Apple. Prior to his current role, Anirudh worked as a PhD Research Intern at Intel, where he developed algorithms for derivative-free optimization in high dimensions with applications to black-box policy search in reinforcement learning. He worked with Vladlen Koltun and Ozan Sener at Intelligent Systems Group in Intel Labs. Anirudh also has experience as a Graduate Research Assistant at National Robotics Engineering Center, NREC where he developed the motion planning and high-level decision stack for a large-scale truck unloading robot in collaboration with Honeywell Intelligrated. He worked with Oren Salzman at NREC. Anirudh has a Doctor of Philosophy - PhD in Robotics from Carnegie Mellon University, where he also earned his Master's Degree in Robotics. Prior to that, he earned a Bachelor of Technology (B.Tech.) in Computer Science from the Indian Institute of Technology, Bombay. Anirudh's tech stack includes research scientist, reinforcement learning, and search. With 1.85 years of relevant experience, he is a highly skilled roboticist with a proven track record of developing innovative solutions for complex problems.