Data Structures and Algorithms

Michael Mitzenmacher is a professor of computer science and area dean for computer science in the School of Engineering and Applied Sciences at Harvard University. Mitzenmacher's research focuses on algorithms for the internet, and he has authored or co-authored more than 150 conference and journal publications on subjects including peer-to-peer networks, power laws, Internet auctions, forward-error correction, and measurement mechanisms for network routers. His work on low-density parity-check codes won both the 2002 Institute of Electrical and Electronics Engineers's Information Theory Society Best Paper Award and the 2009 SIGCOMM Test of Time Award. His textbook on probabilistic techniques in computer science was published in 2005 by Cambridge University Press.

Mitzenmacher graduated summa cum laude with a degree in mathematics and computer science from Harvard. After studying math for a year in Cambridge, England, on the Churchill Scholarship, he obtained his PhD in computer science at U.C. Berkeley. He worked at Digital Systems Research Center before joining the Harvard faculty in 1999.

Sitan Chen is Assistant Professor of Computer Science at Harvard University, where he is a member of the Theory of Computation, the Machine Learning Foundations group, and the Harvard Quantum Initiative. Previously, he was an National Science Foundation (NSF) math postdoctoral researcher at the University of California, Berkeley, after completing his PhD in electrical engineering and computer science (EECS) at the Massachusetts Institute of Technology (MIT) in 2021. He is broadly interested in algorithmic questions about learning from data, most recently related to the science and theory of diffusion generative modeling, and the design of quantum protocols for learning about the physical universe. His work has been recognized with an NSF CAREER award, an ICML Outstanding Paper Award, and the Harvard Dean's Competitive Fund for Promising Scholarship.