Jesse Goodman

about

I am a Postdoctoral Fellow at UT Austin, hosted by David Zuckerman. I recently received my PhD in computer science from Cornell University, where I was advised by Eshan Chattopadhyay. Before that, I was an undergraduate student at Princeton University, and received a BSE in computer science.

My primary interests lie in combinatorics, complexity theory, and pseudorandomness.

thesis

• Seedless Extractors
  Jesse Goodman
  PhD Thesis, Cornell University 2023

publications

• Extractors for polynomial sources over F₂
  Eshan Chattopadhyay, Jesse Goodman, Mohit Gurumukhani
  ITCS 2024


• Low-degree polynomials extract from local sources
  Omar Alrabiah, Eshan Chattopadhyay, Jesse Goodman, Xin Li, João Ribeiro
  ICALP 2022


• The space complexity of sampling
  Eshan Chattopadhyay, Jesse Goodman, David Zuckerman
  ITCS 2022 [video]


• Affine extractors for almost logarithmic entropy
  Eshan Chattopadhyay, Jesse Goodman, Jyun-Jie Liao
  FOCS 2021


• Improved extractors for small-space sources
  Eshan Chattopadhyay, Jesse Goodman
  FOCS 2021 [video]


• Extractors and secret sharing against bounded collusion protocols
  Eshan Chattopadhyay, Jesse Goodman, Vipul Goyal, Ashutosh Kumar, Xin Li, Raghu Meka, David Zuckerman (merge of [CGGL] and [KMZ])
  FOCS 2020 [video]


• Extractors for adversarial sources via extremal hypergraphs
  Eshan Chattopadhyay, Jesse Goodman, Vipul Goyal, Xin Li
  STOC 2020 [video]


• On the approximability of Time Disjoint Walks
  Alexandre Bayen, Jesse Goodman, Eugene Vinitsky
  Journal of Combinatorial Optimization 2020

teaching

• CS 4820 (Introduction to Analysis of Algorithms), Spring 2023, TA, Cornell
• CS 4820 (Introduction to Analysis of Algorithms), Spring 2019, TA, Cornell
• CS 4820 (Introduction to Analysis of Algorithms), Fall 2018, TA, Cornell
• MAT 375 (Introduction to Graph Theory), Spring 2017, TA, Princeton
• Princeton Splash 2017, Berkeley Splash 2018