Experience
Education
Bio
I am interested in a variety of topics in theoretical computer science and machine learning.
My best works have been around online decision making, with a couple of solutions to long-standing problems (minimax rate for multi-armed bandits and linear bandits at COLT 2009/COLT 2012/ALT 2018, best of both worlds for multi-armed bandits at COLT 2011, bandit convex optimization at COLT 2016/STOC 2017, progress on k-server and metrical task systems at STOC 2017/SODA 2018, chasing convex bodies at STOC 2019, multiplayer multi-armed bandit at COLT 2020).
I also did a couple of works in convex optimization (entropic barrier at COLT 2015, geometric view on acceleration in 2015, optimal distributed rates at ICML 2017/NIPS 2018/NeurIPS 2019/ICML 2020) and in network analysis (influence of the seed in preferential attachment graphs, and dimension estimation in random geometric graphs, work done in 2013/2014, appeared in Random Structures and Algorithms). Some other fun side projects included Langevin diffusion (NIPS 2015), entropic CLT (International Mathematics Research Notices 2016), smoothed analysis of local search (STOC 2017), adversarial examples in ML (ICML 2019/NeurIPS 2019) and finding critical points on non-convex functions in low dimensions (COLT 2020).