PeopleofSuperintelligence

Researcher

Christopher Liaw

Also known as Chris Liaw

Christopher Liaw is a researcher whose work connects machine learning theory with privacy, optimization and online markets. He coauthored a NeurIPS Best Paper Award paper on Gaussian mixtures in 2018 and won the Canadian Mathematical Society's Blair Spearman Doctoral Prize for his UBC dissertation in 2021. His research includes private Gaussian-mixture learning, automated bidding and auction design, and submodular algorithms for noisy values. In 2025 and 2026, he coauthored studies of advertiser incentives and two-sided markets; he is a research scientist at Google, with interests in randomized algorithms, machine learning theory and mechanism design.

Now at
Google
Badges

Timeline

  1. 2018

    A NeurIPS Best Paper Award

    In 2018, he coauthors “Nearly Tight Sample Complexity Bounds for Learning Mixtures of Gaussians via Sample Compression Schemes”; the paper wins a NeurIPS Best Paper Award. It gives nearly tight sample-complexity bounds for learning Gaussian mixtures.

  2. 2021

    The Blair Spearman Prize

    In 2021, he wins the Canadian Mathematical Society's Blair Spearman Doctoral Prize for his UBC PhD dissertation, Optimal Algorithms for Experts and Mixtures of Gaussians. At UBC's Department of Computer Science, he pursues a PhD with Nick Harvey as his advisor.

  3. July 2021

    A Toronto theory postdoc

    In July 2021, he works as a postdoctoral researcher in the University of Toronto's Theory Group, hosted by Sasho Nikolov.

  4. 2024

    Private Gaussian mixture learning

    With Mohammad Afzali and Hassan Ashtiani, he develops a method to estimate Gaussian mixtures under differential privacy. Their 2024 paper gives the first finite sample-complexity upper bound for this problem without structural assumptions on the mixtures.

  5. 2024

    A survey of autobidding

    In 2024, he and his coauthors publish an ACM SIGecom Exchanges survey on automated bidding for online advertising. They cover bidding algorithms, equilibrium analysis, auction-format efficiency, and auction design.

  6. 2025

    Submodular maximization under noise

    In 2025, he coauthors a NeurIPS paper that converts robust submodular maximization algorithms for exact value oracles into noisy-value-oracle algorithms while keeping their approximation guarantees.

  7. 2025–2026

    Two autobidding studies

    The 2025 paper “Risk-Averse and Optimistic Advertiser Incentive Compatibility in Auto-bidding” introduces risk-averse and optimistic definitions of advertiser incentive compatibility; Google lists it among its accepted ICML 2026 papers. In 2026, he coauthors “Two-sided Market Design Meets Autobidding,” which opens the study of two-sided markets with autobidders.

  8. As of October 2026

    Google research scientist

    As of October 2026, he is a research scientist at Google. He is broadly interested in randomized algorithms, machine learning theory, and mechanism design.

Career

  1. NowGoogleResearch Scientist
  2. From 2021University of TorontoPostdoctoral Researcher

Education

  1. 2021University of British ColumbiaPhD

From the biography.

  1. 16% of AI career moves in the 2020s went from a university to a companyIncludes Christopher Liaw. We estimate that 16% of AI career moves in the 2020s went from a university to a company; 29% of moves starting at a university went to a company, and 76% ended the university role.
  2. Google had the most people shaping AI every year from 2014 to 2025Includes Google. 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. Google has the highest combined h-index among AI organizationsIncludes Google. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.
  4. 20% of people at companies who shape AI also hold a university role, led by Google and Stanford UniversityIncludes Google. 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.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Christopher Liaw yet. Send us a free-licensed photo.

  1. Awards | NeurIPS 2018 neurips.cc. Checked 22 October 2026.
  2. CS Professor Nick Harvey & PhD Student Christopher Liaw win NeurIPS 2018 Best Paper Award | Computer Science at UBC cs.ubc.ca. Checked 22 October 2026.
  3. An optimal mix of solutions wins PhD grad an optimal prize | Computer Science at UBC cs.ubc.ca. Checked 22 October 2026.
  4. About Me - Chris Liaw’s web page cvliaw.github.io. Checked 22 October 2026.
  5. Mixtures of Gaussians are Privately Learnable with a Polynomial Number of Samples proceedings.mlr.press. Checked 22 October 2026.
  6. Auto-bidding and Auctions in Online Advertising: A Survey research.google. Checked 22 October 2026.
  7. A Unified Approach to Submodular Maximization Under Noise arxiv.org. Checked 22 October 2026.
  8. Risk-Averse and Optimistic Advertiser Incentive Compatibility in Auto-bidding arxiv.org. Checked 22 October 2026.
  9. Google at ICML 2026 research.google. Checked 22 October 2026.
  10. Two-sided Market Design Meets Autobidding arxiv.org. Checked 22 October 2026.