I am a fifth-year PhD student advised by Prof. Russell Impagliazzo. My primary research interests include learning theory and complexity theory, including replicable learning algorithms and boosting.

I plan on graduating in Fall 2023. Please reach out via email!

See my Graduating Bits (a 2-slide presentation summarizing my research work and employment goals)

Publications

DBLP   Arxiv

• STOC'23 "Stability is Stable: Connections between Replicability, Privacy, and Adaptive Generalization". M. Bun, M. Gaboardi, M. Hopkins, R. Impagliazzo, R. Lei, T. Pitassi, S. Sivakumar, J. Sorrell. Proceedings of the 55th Annual ACM SIGACT Symposium on Theory of Computing
  Arxiv Version (Full Paper)
  Also accepted in the non-archival track of FORC 2023
  Selected for an oral presentation at TPDP 2023
• STOC'22 "Reproducibility in Learning". R. Impagliazzo, R. Lei, T. Pitassi, J. Sorrell. Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing
  Our Arxiv Version is slightly more up-to-date; namely, it includes the "reproducibility" to "replicability" name change.
  An earlier version of this work appeared in TPDP 2021
• COLT'21 "Boosting in the Presence of Massart Noise". I. Diakonikolas, R. Impagliazzo, D. M. Kane, R. Lei, J. Sorrell, C. Tzamos. Proceedings of the 34th Annual Conference on Learning Theory
  Arxiv Version
  

Note: In the theoretical computer science community, author order is typically alphabetical and denotes equal contribution.