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Research

I study computational complexity theory. I'm especially interested in pseudorandomness, derandomization, and circuit complexity. Click here to see a poster-style image from February 2024 summarizing my research areas.

Click here for a short explanation of what "derandomization" means (for curious outsiders).

Some algorithms use randomness to solve computational problems. For example, one of the best methods known for finding a large prime number is to pick a large number at random, check if it's prime, and try again if necessary.

You can think of randomness as a scarce computational resource — a type of algorithmic "fuel." Randomized algorithms are okay, but all else being equal, an algorithm that uses fewer random bits is better than an algorithm that uses more random bits, just like a faster algorithm is better than a slower algorithm, or a car that uses less gasoline is better than a car that uses more gasoline. Algorithms that don't use any randomness ("deterministic" algorithms) are best of all. For example, it would be nice to have a fast deterministic algorithm for finding large prime numbers. "Derandomization" is the art of converting randomized algorithms into deterministic algorithms.

One approach for using fewer random bits is to design pseudorandom generators, which use a small number of random bits to generate a long sequence of bits that "look random" and can often be used as a substitute for truly random bits. I'm especially interested in pseudorandom generators that are provably correct.

My research papers are listed below. If you have a question or comment, please send me an email! Like most researchers, I like getting emails about my work.


Surveys, etc.

  1. Paradigms for Unconditional Pseudorandom Generators
    Pooya Hatami and William M. Hoza
    FnT TCS 2024
  2. Recent Progress on Derandomizing Space-Bounded Computation
    William M. Hoza
    BEATCS 2022
  3. Derandomizing Space-Bounded Computation via Pseudorandom Generators and their Generalizations
    William M. Hoza
    PhD dissertation 2021

Ordinary research papers

  1. A Technique for Hardness Amplification Against \(\mathsf{AC}^0\)
    William M. Hoza
    Manuscript 2023
  2. Weighted Pseudorandom Generators via Inverse Analysis of Random Walks and Shortcutting
    Lijie Chen, William M. Hoza, Xin Lyu, Avishay Tal, and Hongxun Wu
    FOCS 2023
  3. Depth-\(d\) Threshold Circuits vs. Depth-\((d + 1)\) AND-OR Trees
    Pooya Hatami, William M. Hoza, Avishay Tal, and Roei Tell
    STOC 2023
  4. Hitting Sets for Regular Branching Programs
    Andrej Bogdanov, William M. Hoza, Gautam Prakriya, and Edward Pyne
    CCC 2022
  5. Better Pseudodistributions and Derandomization for Space-Bounded Computation
    William M. Hoza
    RANDOM 2021ToC (special issue for RANDOM 2021, to appear)
  6. Fooling Constant-Depth Threshold Circuits
    Pooya Hatami, William M. Hoza, Avishay Tal, and Roei Tell
    FOCS 2021
  7. Pseudorandom Generators for Unbounded-Width Permutation Branching Programs
    William M. Hoza, Edward Pyne, and Salil Vadhan
    ITCS 2021
  8. Hitting Sets Give Two-Sided Derandomization of Small Space
    Kuan Cheng and William M. Hoza
    CCC 2020ToC 2022 (special issue for CCC 2020)
  9. Log-Seed Pseudorandom Generators via Iterated Restrictions
    Dean Doron, Pooya Hatami, and William M. Hoza
    CCC 2020
  10. Near-Optimal Pseudorandom Generators for Constant-Depth Read-Once Formulas
    Dean Doron, Pooya Hatami, and William M. Hoza
    CCC 2019
  11. Simple Optimal Hitting Sets for Small-Success RL
    William M. Hoza and David Zuckerman
    FOCS 2018SICOMP 2020
  12. Typically-Correct Derandomization for Small Time and Space
    William M. Hoza
    CCC 2019
  13. Quantum Communication-Query Tradeoffs
    William M. Hoza
    Manuscript 2017
  14. Universal Bell Correlations Do Not Exist
    Cole A. Graham and William M. Hoza
    PRL 2017
  15. Preserving Randomness for Adaptive Algorithms
    William M. Hoza and Adam R. Klivans
    RANDOM 2018
  16. Targeted Pseudorandom Generators, Simulation Advice Generators, and Derandomizing Logspace
    William M. Hoza and Chris Umans
    STOC 2017SICOMP 2022 (special section for STOC 2017)
  17. The Adversarial Noise Threshold for Distributed Protocols
    William M. Hoza and Leonard Schulman
    SODA 2016

I'm grateful for all the mentorship I've received over the years, especially from David Zuckerman (my graduate advisor), Avishay Tal (a postdoc mentor), and Leonard Schulman and Chris Umans (undergraduate research mentors).