I'm a Ph.D. student in Computer Science at Rice University under the supervision of Dr. Anshumali Shrivastava. I received my B.S. from University of California, Berkeley in 2015. My mentors were Dr. Sara Alspaugh, Dr. Kaifei Chen and my advisor was Dr. Randy Katz.
My research focuses on large-scale machine learning. Specifically, I design and optimize randomized hashing algorithms for efficient, accurate and secure representation of data.
Beidi Chen, Yingchen Xu, and Anshumali Shrivastava. "LSH-SAMPLING BREAKS THE COMPUTATIONAL CHICKEN-AND-EGG LOOP IN ADAPTIVE STOCHASTIC GRADIENT ESTIMATION."
Beidi Chen, M. Sadegh Riazi, Anshumali Shrivastava, DanWallach, Farinaz Koushanfar. "Sub-linear Privacy-preserving Search with Untrusted Server and Semi-honest Parties".
Beidi Chen, Anshumali Shrivastava. " Revisiting Winner Take All (WTA) Hashing for Sparse Datasets". In Proceedings of the 34th Conference in Uncertainty in Artificial Intelligence, Aug. 2018. Monterey, California.
Beidi Chen, Anshumali Shrivastava, Rebecca C. Steorts. "Unique Entity Estimation with Application to the Syrian Conflict". The Annals of Applied Statistics 12.2 (2018). (Also Won IISA 2018 Best Student Paper in Applied Statistics with this paper.)
Kaifei Chen, Siyuan He, Beidi Chen, John Kolb, Randy H. Katz, David E. Culler. "BearLoc: A Composable Distributed Framework for Indoor Localization Systems". In Proceedings of the 2015 Workshop on IoT challenges in Mobile and Industrial Systems, IoT-Sys@MobiSys 2015, pages 7-12, May. 2015. Florence, Italy.
S. Alspaugh, Beidi Chen, Jessica Lin, Archana Ganapathi, Marti Hearst, and Randy Katz. "Analyzing Log Analysis: An Empirical Study of User Log Mining". In Proceedings of the 28th Large Installation System Administration Conference (LISA14), pages 62-77, Nov. 2014. Seattle, WA. (Best Student Paper)