Daniel Reichman

Daniel Reichman is an Assistant Professor at the Department of Computer Science, Worcester Polytechnic Institute (WPI). Prior to this role, he pursued postdoctoral research at Cornell University, University of California, Berkeley, and Princeton University. He earned his Ph.D. at the Weizmann Institute under the supervision of Uri Feige.

His research spans machine learning, neural networks, artificial intelligence, and cognitive science. He actively explores computational complexity in neural network structures, interactive proofs in game theory, and theoretical aspects of optimization algorithms. His recent work includes publications in top-tier venues like Nature Human Behaviour, COLT, and ISIT.

Ongoing projects include analyzing time lower bounds for the Metropolis process, depth separations in neural networks, and complexity of counting linear regions. He contributes to academic communities as an Area Chair at AISTATS 2023 and 2024 and participates in conferences like RANDOM and COLT.