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People solve challenging computational problems every day, making predictions about future events, learning new causal relationships, and discovering objects categorized into distinct classes. My research investigates the possible and examines the nature underlying computational problems, including how they relate to aspects of human behavior that arise from approximating optimal solutions to these problems. The issues people face in everyday life often require inductive reasoning, making inferences from limited data under a range of constrained hypotheses. My approach involves drawing on methods developed in statistics, machine learning, and artificial intelligence. By exploring these methods, I establish connections between human cognition and formal techniques, leveraging insights gained from studying human behavior to enhance our understanding of computational challenges.
GRE scores are not accepted. Ph.D. is the primary degree; students are not required to hold an M.S.E. prior to admission.