PeopleofSuperintelligence

Lab leader

Ed Chi

Also known as Ed H. Chi, Ed Huai-Hsin Chi, 紀懷新

Ed Chi's work connects machine learning, social computing and recommender systems. He earned three degrees at the University of Minnesota, led the Augmented Social Cognition group at PARC and then led recommendation work at Google. In 2018, he coauthored Latent Cross for YouTube; in 2023, he co-led Gemini App Research for Gemini 1.0's multimodal model family. ACM named him a Fellow in 2022 for contributions to machine learning and data mining for social computing and recommender systems. As of October 2026, he is Vice President of Research at Google DeepMind, leading research on language models and machine learning.

Works
300

Publication numbers from OpenAlex, as of 14 October 2026. Citations and h-index are hidden because this OpenAlex record may be incomplete or mix in other authors.

Photo of Ed Chi

Timeline

  1. 1992–1999

    Degrees at Minnesota

    He earns a bachelor's degree in computer science in 1994, a master's degree in computer science in 1996, and a PhD in computer and information science in 1999, all at the University of Minnesota.

  2. 2007–2011

    Leading social computing at PARC

    From 2007 to 2011, he serves as area manager and principal scientist at the Palo Alto Research Center's Augmented Social Cognition group, leading research into how social systems help groups remember, think and reason.

  3. 2011–2015

    Google social computing research

    In 2011, he joins Google as a staff research scientist and tech lead, leading work on social search, recommendation, machine learning and crowdsourcing.

  4. 2015–2018

    Google Play and Latent Cross

    In 2015, he leads Google Play search and recommendation improvements. In 2018, he coauthors Latent Cross, a method for adding context to YouTube's recurrent recommender.

  5. 2022

    An ACM Fellowship

    ACM names him a Fellow in 2022 for contributions to machine learning and data mining techniques for social computing and recommender systems.

  6. 2023

    Gemini App Research

    In 2023, he co-leads Gemini App Research and coauthors the Gemini report, which introduces Gemini 1.0 as a multimodal model family trained across image, audio, video and text.

  7. September 2025

    Leading universal assistants

    In September 2025, he serves as VP of Research at Google DeepMind, leading machine learning teams on large language models and universal assistant agents.

  8. As of October 2026

    Vice president of research

    He is Vice President of Research at Google DeepMind, leading research on large language models and machine learning. In June 2026, he opens COMPUTEX's forum on generative AI and traces its development from recommendation and search systems.

Sources and credits

Photo: research.google; Ed H. Chi; creator not stated. License: Not stated by source. Source: research.google. Cropped to a square and resized. Ask us to remove or replace this photo.

  1. Ed H. Chi - Resume edchi.net. Checked 14 October 2026.
  2. Ed H. Chi edchi.net. Checked 14 October 2026.
  3. Ed H. Chi research.google. Checked 14 October 2026.
  4. Latent Cross: Making Use of Context in Recurrent Recommender Systems research.google. Checked 14 October 2026.
  5. Ed Huai-Hsin Chi en.wikipedia.org. Checked 14 October 2026.
  6. [2312.11805] Gemini: A Family of Highly Capable Multimodal Models arxiv.org. Checked 14 October 2026.
  7. Gemini: A Family of Highly Capable Multimodal Models arxiv.org. Checked 14 October 2026.
  8. Seminar: The Future of Personalized Universal Assistant iis.sinica.edu.tw. Checked 14 October 2026.
  9. From Universal Assistants to Multi-Agent Automated Workflows: Generative AI and Intelligent Content Applications at COMPUTEX computexdaily.com. Checked 14 October 2026.