Colin White


I design algorithms that create advanced AI algorithms.

I am Head of Research at Abacus.AI in San Francisco. Our work focuses on automating the search for high-performing deep learning models, as well as explaining and de-biasing them, from both a theoretical and empirical lens. Much of my work involves designing innovative methods by drawing insights from large-scale studies (ref1, ref2, ref3) and designing tools for better benchmarking of machine learning techniques (ref4, ref5, ref6).

I graduated from Carnegie Mellon University with a Ph.D. in computer science, advised by Nina Balcan and supported by the NDSEG Fellowship. I received my undergraduate degree from Amherst College.

For more, see my CV (last updated Oct. 2022).


    • • Jan 25, 2023: I am giving a talk at UC Berkeley. My slides are here.
    • • Jan 22, 2023: New survey on neural architecture search. Email me if you have comments!
    • • Jan 11, 2023: I gave a talk at Caltech. My slides are here.
    • • Dec 1, 2022: I am a Program Chair for AutoML 2023 in Potsdam/Berlin, Germany. Submit your paper by March 23, 2023!
    • • Oct 11, 2022: I gave a talk at the AutoML Fall School 2022. My slides are here.
    • • Aug 17, 2022: I gave a talk at Microsoft Research. See the slides here.
    • • Jul 25, 2022: I gave a tutorial on neural architecture search with Debadeepta Dey, at AutoML 2022. View the talk here, and the slides here.




  • Local Chair and Area Chair for AutoML 2022.
    Co-organizer for the 8th AutoML Workshop at ICML 2021.
    Top 10% of reviewers at NeurIPS 2022
    Top 10% of reviewers at ICML 2022
    Top 10% of reviewers at ICLR 2022
    Top 10% of reviewers at NeurIPS 2021
    Top 10% of reviewers at ICML 2021
    Top 10% of reviewers at NeurIPS 2020
    Top 50% of reviewers at NeurIPS 2019