PeopleofSuperintelligence

Researcher

Aidan Perreault

Aidan Perreault is a computer science researcher whose work covers unsupervised learning, decision-focused distribution comparison, and protein engineering. At Northwestern, he earned undergraduate mathematics honors and the Corbin Prize; Stanford admitted him to its computer science Ph.D. program in Autumn 2019. He coauthored work on smoothed analysis and protein evolution, and his 2022 paper on distribution comparison won an ICLR Outstanding Paper Award. As of October 2026, he is a Ph.D. student and a master's student in computer science at Stanford.

Timeline

  1. 2015–2016

    A first-year mathematics award

    He earns Northwestern's Outstanding Achievement in Mathematics award as a first-year student in 2015–2016.

  2. 2017–2018

    A junior mathematics award

    He earns Northwestern's Outstanding Achievement in Mathematics award as a junior in 2017–2018.

  3. 2018

    Smoothed analysis by decoupling

    In 2018, he coauthors Smoothed Analysis in Unsupervised Learning via Decoupling, which gives the first polynomial-time guarantees for learning overcomplete hidden Markov models under smoothed analysis.

  4. 2018–2019

    A senior mathematics honor

    He receives an honorable mention for achievement in mathematics as a senior in 2018–2019.

  5. 2019

    A Corbin Prize

    In 2019, he receives the Franklin N. and Lee L. Corbin Prize from Weinberg College of Arts and Sciences. The award goes to seniors with outstanding academic records who plan to attend graduate or professional school.

  6. 2022

    An ICLR Outstanding Paper Award

    He coauthors Comparing Distributions by Measuring Differences that Affect Decision Making, which compares distributions through the optimal loss for a decision task. The paper receives an ICLR Outstanding Paper Award in 2022.

  7. 2023

    MCMC for protein evolution

    In 2023, he coauthors Plug & Play Directed Evolution of Proteins with Gradient-Based Discrete MCMC. Its sampler combines unsupervised protein language models with supervised models that predict protein function from sequence, then uses gradients to propose mutations.

  8. As of October 2026

    Computer science at Stanford

    He is a Ph.D. student in computer science at Stanford, admitted in Autumn 2019, and a master's student in the field, admitted in Winter 2025.

Career

Education

  1. From 2025Stanford UniversityMaster’s
  2. From 2019Stanford UniversityPhD
  3. Northwestern UniversityUndergraduate student

From the biography.

  1. 20% of people at companies who shape AI also hold a university role, led by Google and Stanford UniversityIncludes Stanford University. We estimate that 539 of the 6,766 people with a known current organization (8%) hold both a university role and a company role, including 20% of people at companies and 13% of people at universities.
  2. Google had the most people shaping AI every year from 2014 to 2025Includes Stanford University. Our estimates of which organizations employed the most people shaping AI each year from 1955 to 2025, tracing the shift from university labs to companies.
  3. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Stanford University. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  4. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes Stanford University. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.

Sources and credits

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  1. 2003-2025: Department of Mathematics - Northwestern University math.northwestern.edu. Checked 21 October 2026.
  2. Smoothed Analysis in Unsupervised Learning via Decoupling | arXiv arxiv.org. Checked 21 October 2026.
  3. News 2019: Department of Mathematics - Northwestern University math.northwestern.edu. Checked 21 October 2026.
  4. Announcing the ICLR 2022 Outstanding Paper Award Recipients – ICLR Blog blog.iclr.cc. Checked 21 October 2026.
  5. Plug & Play Directed Evolution of Proteins with Gradient-Based Discrete MCMC: Article No. 025014 - National Laboratory of the Rockies research-hub.nlr.gov. Checked 21 October 2026.
  6. Browse Computer Science | Stanford Profiles profiles.stanford.edu. Checked 21 October 2026.