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Tesca Fitzgerald is a Professor in the Department of Computer Science at Yale University. Her research broadly focuses on interactive robot learning, cognitive robotics, human-robot interaction, transfer learning, and active learning. She aims to advance the adaptive capacities of robots, which are increasingly essential for handling novel objects, tasks, and interactions in everyday life. Rather than only preparing robots for predefined tasks, her work develops robust systems that can assume and adapt to unforeseen situations with the aid of human teachers’ domain knowledge. Fitzgerald's research addresses the challenges posed by novelty in robotic learning, including the implications and causes of novelty within robotic systems, and how to structure human-teacher interactions to achieve effective learning goals. She has received multiple prestigious awards for her academic contributions, including the National Science Foundation Graduate Research Fellowship and the IBM Ph.D. Fellowship. Fitzgerald has published numerous papers in leading journals and conferences, contributing significantly to the field of robotics and artificial intelligence.
Administered via the Graduate School of Arts and Sciences (GSAS). GRE General is optional for PhD.