PeopleofSuperintelligence

Researcher

Aja Huang

Also known as 黃士傑

Aja Huang is a computer scientist whose work includes computer Go, reinforcement learning, and AI for mathematics and algorithms. He developed the Go program Erica while studying in Taiwan; it defeated Zen and won gold at the Computer Olympiad. After joining DeepMind in 2012, he became a key AlphaGo developer and contributed to AlphaGo Zero, AlphaStar, AlphaTensor, and AlphaProof. At the 2024 IMO, AlphaProof and AlphaGeometry 2 reached silver-medal level; by May 2026, Huang had joined the AlphaEvolve team to scale its impact.

Works
10
Citations
28,682
h-index
7

Publication numbers from OpenAlex, as of 14 October 2026.

Timeline

  1. 2001–2011

    A Go engine in Taiwan

    He earned a bachelor's degree at National Chiao Tung University in 2001, then a master's degree in 2003 and a doctorate in 2011 at National Taiwan Normal University. During his doctoral study, he developed Erica, a Go program that defeated Zen and won gold at the Computer Olympiad.

  2. 2012–2016

    Programming for the AlphaGo match

    In 2012, he joined DeepMind, where he and David Silver were head programmers. By March 2016, he was a key AlphaGo developer as the system played Lee Sedol in Seoul.

  3. 2017

    Learning Go by self-play

    AlphaGo Zero learned Go from self-play, starting with random play and no human Go games. Huang was among the contributors to the system.

  4. 2019

    Reaching Grandmaster in StarCraft

    AlphaStar reached Grandmaster level in full StarCraft II through multi-agent learning, reinforcement learning, and imitation learning. Huang was listed on its research team.

  5. 2022

    Finding new matrix algorithms

    AlphaTensor used reinforcement learning to discover more efficient matrix multiplication algorithms. Huang contributed to the research team behind the system.

  6. 2024

    Formal mathematics at the IMO

    Together, AlphaProof and AlphaGeometry 2 solved four of six 2024 IMO problems, reaching silver-medal performance. Huang made key contributions to AlphaProof, a reinforcement-learning system for formal mathematical reasoning.

  7. By May 2026

    Scaling AlphaEvolve's impact

    By May 2026, Huang had joined the AlphaEvolve team after its initial development and contributed to scaling its impact. AlphaEvolve is a Gemini-powered coding agent for designing advanced algorithms and supporting new discoveries in mathematics and computer science.

Sources and credits

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  1. Aja Huang - Wikipedia en.wikipedia.org. Checked 14 October 2026.
  2. NTNU’s Huang key to AI go challenge taipeitimes.com. Checked 14 October 2026.
  3. AlphaGo Zero: Starting from scratch — Google DeepMind deepmind.google. Checked 14 October 2026.
  4. AlphaStar: Grandmaster level in StarCraft II using multi-agent reinforcement learning — Google DeepMind deepmind.google. Checked 14 October 2026.
  5. Discovering novel algorithms with AlphaTensor — Google DeepMind deepmind.google. Checked 14 October 2026.
  6. AI achieves silver-medal standard solving International Mathematical Olympiad problems — Google DeepMind deepmind.google. Checked 14 October 2026.
  7. AlphaEvolve: How our Gemini-powered coding agent is scaling impact across fields — Google DeepMind deepmind.google. Checked 14 October 2026.