Ravi Kumar

Ravi Kumar

Google

Mountain View, CA

I obtained my PhD in Computer Science from Cornell University and have previously worked at IBM Almaden and Yahoo! Research. My broad interests include algorithms for massive data, ML/privacy, and the theory of computation. I can be reached at ravi.k53 on Gmail; I am also on Facebook, LinkedIn, Twitter, though I use them sparingly. I live and work in the beautiful SF Bay area.

Recent papers (fuller list at DBLP, Scholar, AMiner)

• • Faster privacy accounting via evolving discretization (w/ B. Ghazi, P. Kamath, P. Manurangsi), ICML 2022

  • Parsimonious learning-augmented caching (w/ S. Im, A. Petety, M. Purohit), ICML 2022

  • RUMs from head-to-head contests (w/ M. Almanza, F. Chierichetti, A. Panconesi, A. Tomkins), ICML 2022

  • The Gibbs--Rand model (w/ F. Chierichetti, S. Lattanzi), PODS 2022

  • Distributed, private, sparse histograms in the two-server model (w/ J. Bell, A. Gascon, B. Ghazi, P. Manurangsi, M. Raykova, P. Schoppmann), CCS 2022