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Alex Bridgland

Alex Bridgland is an AI engineer whose work spans protein-structure prediction and generative protein design. At DeepMind, he coauthored the AlphaFold research presented at CASP14, shared equal-contributor credit on its 2021 Nature paper, and helped bring predictions to proteome scale. He later coauthored AlphaFold 3 for biomolecular-complex prediction, then Latent-X for protein-binder design and Latent-Y for antibody campaigns. As of October 2026, he is a Founding Member of Technical Staff at Latent Labs.

Works
11
Citations
70,164
h-index
9
Rankings
#51 by citations since 2021
Badges

Publication numbers from OpenAlex, as of 18 October 2026.

Timeline

  1. 2020

    AlphaFold at CASP14

    In 2020, he coauthors DeepMind’s AlphaFold report for CASP14; the system scores a median 92.4 GDT across all targets.

  2. 2021

    Equal credit on AlphaFold

    In 2021, he shares equal-contributor credit on Nature’s AlphaFold paper, which reports accuracy competitive with experimental structures in a majority of CASP14 cases.

  3. 2021

    Predictions at proteome scale

    In 2021, he coauthors a DeepMind report on applying AlphaFold at whole-proteome scale; the team shares its predictions through AlphaFold DB with EMBL-EBI.

  4. 2024

    AlphaFold 3 predicts complexes

    In 2024, he coauthors AlphaFold 3, a diffusion-based model that predicts joint structures for complexes containing proteins, nucleic acids, small molecules, ions and modified residues.

  5. 2025

    Latent-X designs binders

    In 2025, he coauthors Latent-X, a model that generates all-atom structures and sequences for protein binders from target protein epitopes.

  6. 2026

    Latent-Y runs antibody campaigns

    In 2026, he coauthors Latent-Y, an AI agent that runs antibody-design campaigns from text prompts through literature review, target analysis, candidate design, computational validation, and selection of lab-ready sequences.

  7. As of October 2026

    Technical staff at Latent Labs

    As of October 2026, he is a Founding Member of Technical Staff at Latent Labs, where he engineers next-generation protein-design systems. His earlier work spans AlphaFold 1, 2 and 3, model building and evaluation, data pipelines, and biological software tools.

A language model matched the links in this timeline to people, organizations and papers (provisional, model-judged).

Career

  1. NowLatent LabsFounding Member of Technical Staff
  2. 2019–2024Google DeepMind

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

Most-cited works

  1. Highly accurate protein structure prediction with AlphaFold2021 · Nature · 43,391 citationsWith Alexander Pritzel, Andrew W. Senior, Anna Potapenko, Bernardino Romera-Paredes, Clemens Meyer and David Silver
  2. Accurate structure prediction of biomolecular interactions with AlphaFold 32024 · Nature · 15,503 citationsWith Alexander Pritzel, Anna Potapenko, Demis Hassabis, John Jumper, Josh Abramson and Max Jaderberg
  3. Protein complex prediction with AlphaFold-Multimer2021 · 3,777 citationsWith Alexander Pritzel, Andrew W. Senior, Anna Potapenko, Demis Hassabis, John Jumper and Olaf Ronneberger
  4. Improved protein structure prediction using potentials from deep learning2020 · Nature · 3,371 citationsWith Andrew W. Senior, David Silver, Demis Hassabis, John Jumper, Karen Simonyan and Koray Kavukcuoglu
  5. Highly accurate protein structure prediction for the human proteome2021 · Nature · 3,004 citationsWith Alexander Pritzel, Andrew W. Senior, Anna Potapenko, Bernardino Romera-Paredes, Clemens Meyer and Demis Hassabis

From OpenAlex, as of 18 October 2026.

  1. 4 of the 25 people with the most-cited recent papers also lead on career citationsIncludes Alex Bridgland. We compare citations to 2023–2025 papers with career citations and h-index, after correcting reviewed publication-date errors: who leads, when they started and where they work.
  2. Google has the highest combined h-index among AI organizationsIncludes Google. Our estimates of combined and median h-index at AI organizations, using current affiliations and OpenAlex records.
  3. Google alumni founded or led 79 other organizations, the most among the labs we compareIncludes Google. We trace 181 organizations founded or led by AI lab alumni, and 187 career moves between the labs.
  4. 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 from 1962 to 2025, with a year-by-year chart.

Colleagues

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

Sources and credits

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  1. AlphaFold: a solution to a 50-year-old grand challenge in biology deepmind.google. Checked 18 October 2026.
  2. Highly accurate protein structure prediction with AlphaFold nature.com. Checked 18 October 2026.
  3. Enabling high-accuracy protein structure prediction at the proteome scale deepmind.google. Checked 18 October 2026.
  4. Accurate structure prediction of biomolecular interactions with AlphaFold 3 nature.com. Checked 18 October 2026.
  5. Latent-X: An Atom-level Frontier Model for De Novo Protein Binder Design arxiv.org. Checked 18 October 2026.
  6. Latent-Y: A Lab-Validated Autonomous Agent for De Novo Drug Design arxiv.org. Checked 18 October 2026.
  7. Our DNA - Latent Labs latentlabs.com. Checked 18 October 2026.
  8. Alex Bridgland - Latent Labs latentlabs.com. Checked 18 October 2026.