PeopleofSuperintelligence

Researcher

Alexander Pritzel

Also known as Alex Pritzel

Alexander Pritzel is an AI researcher whose work spans deep reinforcement learning, protein structure prediction and multimodal AI. He coauthored early control and episodic-learning papers, helped develop AlphaFold, and coauthored Google’s Gemini report. ICLR gave his continuous-control paper its Test of Time Award in 2026. In June 2026, he was a Google researcher involved in training AI systems and expected to move to Anthropic.

Works
40
Citations
83,708
h-index
27

Publication numbers from OpenAlex, as of 14 October 2026.

Timeline

  1. 2016

    Controlling continuous motion

    He coauthored “Continuous control with deep reinforcement learning,” which uses an actor-critic algorithm to learn policies for continuous action spaces.

  2. 2017

    Learning from experience

    He coauthored Neural Episodic Control, a deep reinforcement learning agent designed to rapidly assimilate new experiences and act on them.

  3. 2021

    Predicting protein structures

    The Nature paper he coauthored describes AlphaFold predicting protein structures with accuracy competitive with experimental structures in most cases.

  4. February 2023

    A DeepMind role

    He was a research associate at DeepMind and a co-developer of the AlphaFold program.

  5. December 2023

    Gemini goes multimodal

    He coauthored the Gemini technical report, which introduces a multimodal model family for image, audio, video and text understanding.

  6. 2026

    A decade-later award

    ICLR’s 2026 Test of Time Award recognized the 2016 continuous-control paper he coauthored.

  7. June 2026

    Planning a move

    He was a Google Gemini contributor involved in training AI systems and was set to move to Anthropic.

Sources and credits

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  1. [1509.02971] Continuous control with deep reinforcement learning arxiv.org. Checked 14 October 2026.
  2. Announcing the Test of Time Awards from ICLR 2016 – ICLR Blog blog.iclr.cc. Checked 14 October 2026.
  3. [1703.01988] Neural Episodic Control arxiv.org. Checked 14 October 2026.
  4. Highly accurate protein structure prediction with AlphaFold | Nature nature.com. Checked 14 October 2026.
  5. CAS: The Impact of Alphafold on Protein Research - LMU Munich lmu.de. Checked 14 October 2026.
  6. [2312.11805] Gemini: A Family of Highly Capable Multimodal Models arxiv.org. Checked 14 October 2026.
  7. Google hit by new AI brain drain as Anthropic poaches top Gemini talent - Los Angeles Times latimes.com. Checked 14 October 2026.