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Daniel Rakita is a Professor at Yale Engineering, specializing in motion planning and optimization algorithms for robot manipulators. He focuses on developing feasible and effective robotic motion strategies that facilitate real-time operation in various applications. His work aims to enhance intuitive control for novice users through shared-control interfaces, making robotic assistance accessible in critical domains such as homecare, telenursing, and disaster response. With a strong background in robotics and computer science, coupled with expertise in human-robot interaction, Rakita employs interdisciplinary techniques to generate generalizable solutions that align with user needs. He has been recognized with multiple awards for his contributions, including the UW-Madison Outstanding Graduate-Student Research Award and various fellowships for his research efforts. His published works have significantly impacted fields related to robotics, showcasing innovations in human-robot collaboration and optimization methodologies.
Administered via the Graduate School of Arts and Sciences (GSAS). GRE General is optional for PhD.