Daniel Rakita

Dr. Daniel Rakita is an Assistant Professor of Computer Science at Yale University, specializing in robotics and human-robot interaction. His research focuses on developing real-time motion planning algorithms and intuitive shared-control interfaces to enable robots to safely assist humans in critical tasks such as healthcare, disaster relief, and manufacturing. He holds a Ph.D. and M.S. in Computer Science from the University of Wisconsin-Madison.

His work integrates robotics, machine learning, and human factors to create end-to-end solutions for robot manipulation. Key contributions include RelaxedIK (real-time collision-free motion synthesis) and CollisionIK (per-instant pose optimization). His research also explores teleoperation systems and adaptive viewpoints for remote control in complex environments.

• Education: Ph.D./M.S., University of Wisconsin-Madison (Computer Science)
• Affiliations: School of Engineering & Applied Science, Yale University
• Labs/Teams: Robotics and Human-Computer Interaction research groups at Yale

His publications span top venues like Robotics: Science and Systems (RSS), ICRA, and HRI. Notable awards include the Microsoft PhD Fellowship (2019-2021) and Best Paper Awards at HRI 2018. Current projects emphasize diffusion policies for manipulation learning and optimization-based motion generation frameworks.