Research

• Recursive lattice reduction--A framework for finding short lattice vectors (with Divesh Aggarwal, Thomas Espitau, and Noah Stephens-Davidowitz)
• Lattice Problems Beyond Polynomial Time (with Divesh Aggarwal, Huck Bennett, Zvika Brakerski, Alexander Golovnev, Rajendra Kumar, Zeyong Li, Noah Stephens-Davidowitz, and Vinod Vaikuntanathan, in STOC'23.)
Revisiting Time-Space Tradeoffs for Function Inversion (with Alexander Golovnev, Siyao Guo, and Noah Stephens-Davidowitz, accepted to CRYPTO'23.)
• On the (im)possibility of branch-and-bound search-to-decision reductions for approximate optimization (with Alexander Golovnev, Siyao Guo, and Noah Stephens-Davidowitz, accepted to APPROX'23)
• Always Asking for Advice is Often Optimal (with Sid Banerjee and Joe Halpern, preprint).
• Reasoning about Causal Models with Infinitely Many Variables (with Joe Halpern, in AAAI'22).
• Causal Models with Infinitely Many Variables for continuous time causal modeling (with Joe Halpern, preprint).

Talks

• STOC 2023 "Lattice Problems beyond Polynomial Time"
• Cornell A Exam, National University of Singapore, MIT, NYU Theory Seminars (slides) "Function Inversion Revisited"
• Cornell Theory Tea (slides) "Always Asking for Advice is Often Optimal"
• Great Ideas in TCS Seminar (slides) "A Beginner's Perspective on Concentration Inequalities"

Teaching

• Head TA, ORIE 4742 (Info Theory and Probabilistic Modeling), Spring 2021
• Part-time TA, CS 4820 (Algorithms), Fall 2020
• Head PhD TA, CS 3110 (Functional Programming), Spring 2020
• (co-)Head TA, CS 2800 (Discrete Structures), Fall 2019

Awards

• 2021 NSF GRFP Honorable Mention
• 2020 Cornell CS Outstanding Teaching Assistant