PeopleofSuperintelligence

Researcher

David Reiman

David Reiman is a researcher whose machine-learning work spans astronomy and protein structure prediction. At UC Santa Cruz, he applied generative networks to blended galaxy images and probabilistic flows to quasar spectra. He later coauthored DeepMind’s reports on AlphaFold, which predict protein structures at scale. In 2024, he contributed to AlphaFold 3 as a Google DeepMind Core Contributor; the model predicts structures of biomolecular complexes.

Works
16
Citations
63,080
h-index
11
Rankings
#63 by citations since 2021
Badges

Publication numbers from OpenAlex, as of 19 October 2026.

Timeline

  1. 2018

    Separating blended galaxies

    In 2018, he and Brett E. Göhre propose a branched generative adversarial network that separates overlapping galaxy images into two reconstructions.

  2. March 2019

    Presenting AstroGANs

    At UC Santa Cruz in March 2019, he is a physics PhD student presenting AstroGANs, which applies generative adversarial networks to deblend galaxy images, improve resolution and infer high-redshift quasar emission.

  3. 2020

    Predicting quasar continua

    With three coauthors, he introduces Spectre in 2020, a normalizing-flow model that predicts quasar continua from red-side spectra and estimates neutral hydrogen from two z>7 quasars.

  4. July 2021

    AlphaFold at proteome scale

    In July 2021, he coauthors DeepMind’s account of AlphaFold at proteome scale. The system uses amino-acid sequences and multiple-sequence alignments to form residue-pair representations and predict protein structures.

  5. May 2024

    AlphaFold 3

    In May 2024, he is a Core Contributor at Google DeepMind and coauthors AlphaFold 3, which predicts the joint structures of complexes containing proteins, nucleic acids, small molecules, ions and modified residues.

Career

  1. 2024Google DeepMindCore Contributor

Education

  1. From 2019University of California, Santa CruzPhD

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 · 43,412 citationsWith Alex Bridgland, Alexander Pritzel, Andrew W. Senior, Anna Potapenko, Augustin Žídek and Bernardino Romera-Paredes
  2. Accurate structure prediction of biomolecular interactions with AlphaFold 32024 · Nature · 15,516 citationsWith Alex Bridgland, Alexander Pritzel, Anna Potapenko, Augustin Žídek, Demis Hassabis and John Jumper
  3. Highly accurate protein structure prediction for the human proteome2021 · Nature · 3,004 citationsWith Alex Bridgland, Alexander Pritzel, Andrew W. Senior, Anna Potapenko, Augustin Žídek and Bernardino Romera-Paredes
  4. Applying and improving AlphaFold at CASP142021 · Proteins Structure Function and Bioinformatics · 397 citationsWith Alex Bridgland, Alexander Pritzel, Andrew W. Senior, Anna Potapenko, Augustin Žídek and Bernardino Romera-Paredes
  5. Addendum: Accurate structure prediction of biomolecular interactions with AlphaFold 32024 · Nature · 338 citationsWith Alex Bridgland, Alexander Pritzel, Anna Potapenko, Augustin Žídek, Demis Hassabis and John Jumper

From OpenAlex, as of 19 October 2026.

  1. The median h-index is 53 at universities and 19 at frontier AI labsIncludes David Reiman. The median h-index is 53 at universities and 19 at frontier AI labs. We compare publishing careers, citations and moves to estimate how universities and frontier labs contribute to AI research.
  2. 4 of the 25 people with the most-cited recent papers also lead on career citationsIncludes David Reiman. 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.
  3. 14% of AI career moves in the 2020s went from a university to a companyIncludes David Reiman. Our estimates of how university-to-company career transitions changed by decade, including roles added alongside an earlier job.
  4. 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.

Colleagues

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

Sources and credits

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

  1. [1810.10098] Deblending galaxy superpositions with branched generative adversarial networks arxiv.org. Checked 19 October 2026.
  2. AAII@UCSC – Page 5 aaii.ucsc.edu. Checked 19 October 2026.
  3. [2006.00615] Fully probabilistic quasar continua predictions near Lyman-α with conditional neural spline flows arxiv.org. Checked 19 October 2026.
  4. Enabling high-accuracy protein structure prediction at the proteome scale — Google DeepMind deepmind.google. Checked 19 October 2026.
  5. Accurate structure prediction of biomolecular interactions with AlphaFold 3 | Nature nature.com. Checked 19 October 2026.