PeopleofSuperintelligence

Researcher

John Nham

John Nham is an artificial intelligence researcher who was one of the 20 authors of the January 2016 Nature paper on AlphaGo at Google. At the Massachusetts Institute of Technology in 2008, they wrote a master's thesis under John N. Tsitsiklis on scheduling policies for heavy-tailed distributions. In the 2016 Nature study, AlphaGo reached a 99.8% winning rate against other Go programs and defeated the European Go champion by 5 games to 0. From 2022 to 2025, they coauthored the Knowledge Prompts paper, the PaLM 2 technical report, the Dr Genre text-rewriting paper and the Gemini 2.5 technical report, and were named as a co-inventor on a 2024 patent application for query intent classification and a 2025 US patent for soft knowledge prompts.

Now at
Google

Timeline

  1. 2008

    Master's thesis at MIT

    At the Massachusetts Institute of Technology in 2008, they write the master's thesis "Size-Independent vs. Size-Dependent Policies in Scheduling Heavy-Tailed Distributions" under the supervision of John N. Tsitsiklis.

  2. January 2016

    AlphaGo in Nature

    In January 2016, Nature publishes "Mastering the game of Go with deep neural networks and tree search", and they are one of its 20 authors, listed at Google in Mountain View, California. The paper's program AlphaGo reaches a 99.8% winning rate against other Go programs and defeats the human European Go champion by 5 games to 0.

  3. October 2022

    Knowledge Prompts paper

    They coauthor "Knowledge Prompts: Injecting World Knowledge into Language Models through Soft Prompts" in October 2022 with Cicero Nogueira dos Santos, Zhe Dong, Daniel Cer, Siamak Shakeri, Jianmo Ni and Yun-hsuan Sung. The paper trains task-independent soft knowledge prompts by self-supervised learning on knowledge-base data so that they work as an external memory and give language models world knowledge.

  4. May 2023

    The PaLM 2 report

    In May 2023, they are listed among the authors of the PaLM 2 Technical Report. The report introduces PaLM 2, a Transformer-based language model trained using a mixture of objectives with better multilingual and reasoning capabilities and greater compute efficiency than its predecessor PaLM.

  5. July 2024

    Query intent classification patent application

    US patent application publication US20240232637A9, "Method for Training Large Language Models to Perform Query Intent Classification", names them as a co-inventor in July 2024. The method trains large language models to perform query intent classification tasks using retrieval augmentation and multi-stage distillation.

  6. March 2025

    Dr Genre for text rewriting

    In March 2025, they are the second author, after Yufei Li, of "Dr Genre: Reinforcement Learning from Decoupled LLM Feedback for Generic Text Rewriting". The paper proposes a decoupled-reward learning framework that uses objective-oriented reward models for generic rewriting and builds the ChatRewrite conversational dataset.

  7. June 2025

    US patent on soft knowledge prompts

    Google's granted US patent 12321706, "Soft knowledge prompts for language models", names them as a co-inventor in June 2025. The patent covers training soft knowledge prompts by self-supervised learning on data from knowledge bases to inject world knowledge into language models.

  8. July 2025

    The Gemini 2.5 report

    They appear in the author list of the Gemini 2.5 technical report in July 2025. The report introduces Gemini 2.5 Pro and Gemini 2.5 Flash alongside the earlier Gemini 2.0 Flash and Flash-Lite models.

  1. 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.
  2. 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.
  3. 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.
  4. Google alumni have founded or led 133 other organizations, more than any other AI labIncludes Google. We estimate that alumni of 17 major AI labs went on to found or lead 350 other organizations, including 226 they founded, and we trace 472 career moves directly between 23 labs since 2010.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

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

  1. John Nham - Google Scholar scholar.google.com. Checked 22 October 2026.
  2. John N. Tsitsiklis - Masters students mit.edu. Checked 22 October 2026.
  3. Mastering the game of Go with deep neural networks and tree search | Nature nature.com. Checked 22 October 2026.
  4. Mastering the game of Go with deep neural networks and tree search research.google. Checked 22 October 2026.
  5. [2210.04726] Knowledge Prompts: Injecting World Knowledge into Language Models through Soft Prompts arxiv.org. Checked 22 October 2026.
  6. [2305.10403] PaLM 2 Technical Report arxiv.org. Checked 22 October 2026.
  7. US20240232637A9 - Method for Training Large Language Models to Perform Query Intent Classification - Google Patents patents.google.com. Checked 22 October 2026.
  8. [2503.06781] Dr Genre: Reinforcement Learning from Decoupled LLM Feedback for Generic Text Rewriting arxiv.org. Checked 22 October 2026.
  9. US12321706B2 - Soft knowledge prompts for language models - Google Patents patents.google.com. Checked 22 October 2026.
  10. [2507.06261] Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities arxiv.org. Checked 22 October 2026.