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Huacheng Yu is an Assistant Professor in the Department of Computer Science at Princeton University, where he has been since 2019. He completed his PhD at Stanford University under the guidance of Ryan Williams and Omer Reingold. His research focuses on data structures, streaming algorithms, communication complexity, and graph algorithms. Before joining Princeton, he was a postdoctoral researcher at Harvard University, working in the Theory of Computation group directed by Jelani Nelson. Yu has contributed to various significant works in theoretical computer science, exploring optimality in static retrieval, adversarial robustness in machine learning contexts, and developing novel streaming algorithms. He has been actively publishing in high-impact conferences such as FOCS, STOC, and SODA, where his work often emphasizes the bounds and efficiencies of various computational problems. Over the years, he has collaborated with multiple researchers, showcasing an ongoing commitment to advancing theoretical frameworks within computer science. Yu's educational contributions include teaching multiple advanced courses in algorithms and data structures. His active engagement in professional service includes roles in program committees for prestigious conferences.
GRE scores are not accepted. Ph.D. is the primary degree; students are not required to hold an M.S.E. prior to admission.