1. In 2018 I participated in RIPS where I worked on deep reinforcement learning sponsored by AMD [pdf] [code]
  2. I spent a summer in the Statistics department of University of Oxford working on interacting particle systems under the supervision of Professor Paul Chleboun [pdf]
  3. I wrote a master’s thesis on branching random walks with selection, supervised by Professor Julien Berestycki [pdf]

notes

  1. Discrete computational optimal transport (with Adam Block) [pdf]
  2. L1-regularized regression [pdf]
  3. Sparse PCA (with Sinho Chewi) [pdf]

presentations

  1. Malliavin Calculus [pdf]
  2. Kernel density estimation via diffusion [pdf]
  3. Normality testing via Wasserstein distance [pdf]
  4. The East-process [pdf]
  5. Branching random walks with selection [pdf]