PeopleofSuperintelligence

Researcher

Bowen Jing

Bowen Jing is an AI researcher whose work applies generative models to biomolecular structure, molecular simulation and protein design. In 2020, he coauthored a paper on geometric vector perceptrons that appeared at ICLR in 2021; he also coauthored ATOM3D, Torsional Diffusion and DiffDock in 2021, 2022 and 2023. He coauthored AlphaFlow for protein ensembles in 2024, ProtComposer for ellipsoid-guided protein design in 2025 and SwitchCraft for state-switching proteins in 2026. He completed a Ph.D. in Computer Science at MIT, co-advised by Tommi Jaakkola and Bonnie Berger, and, as of October 2026, leads the Machine Learning team at Divergence Labs, where the team develops generative models to discover the next generation of antibody therapeutics.

Now at
Divergence Labs

Timeline

  1. 2020–2021

    Geometric vector perceptrons

    He completes a B.S. in Computer Science at Stanford under Ron Dror. In 2020, he coauthors a paper introducing geometric vector perceptrons, which let graph neural networks reason about molecular geometry and relations for protein model assessment and computational design; the paper appears at ICLR in 2021.

  2. 2021

    ATOM3D earns a NeurIPS award

    In 2021, he coauthors ATOM3D, a collection of benchmark datasets for three-dimensional molecules and biopolymers with tools for dataset processing, model training and evaluation. NeurIPS awards it a Datasets & Benchmarks Track Best Paper Award.

  3. 2022

    Torsional diffusion for conformers

    In 2022, he coauthors Torsional Diffusion for Molecular Conformer Generation, a framework that applies diffusion to molecular torsion angles. It generates conformer ensembles and uses exact likelihoods to build a generalizable Boltzmann generator.

  4. 2023

    DiffDock for molecular docking

    In 2023, he coauthors DiffDock, a generative model that treats ligand docking as diffusion over a non-Euclidean manifold of ligand poses. It reaches a 38% top-one success rate on PDBBind at RMSD below 2 Å.

  5. 2024

    AlphaFlow models protein ensembles

    In 2024, he coauthors AlphaFold Meets Flow Matching for Generating Protein Ensembles. The paper fine-tunes AlphaFold and ESMFold with flow matching to create sequence-conditioned protein structure models called AlphaFlow and ESMFlow.

  6. 2025

    ProtComposer and 3D layouts

    In 2025, he coauthors ProtComposer, which generates protein structures from spatial layouts represented by 3D ellipsoids. Users set the location, size, orientation, secondary structure and approximate shape of protein substructures through hand-specified ellipsoids.

  7. 2026

    SwitchCraft designs protein states

    In 2026, he coauthors SwitchCraft, a framework for designing state-switching proteins through compositional design constraints parameterized by structure-prediction models. Its evaluations include allosteric regulation of motifs and discrimination of bound ligand identities.

  8. As of October 2026

    Leads machine learning at Divergence Labs

    As of October 2026, he leads the Machine Learning team at Divergence Labs, which develops and deploys generative models to discover antibody therapeutics. He completes a Ph.D. in Computer Science at MIT, co-advised by Tommi Jaakkola and Bonnie Berger; his thesis focuses on diffusion models for biomolecules and their applications in structure prediction, molecular simulation and protein design.

Career

  1. NowDivergence LabsHead of Machine Learning

Education

  1. Stanford UniversityB.S. in Computer Science
  2. Massachusetts Institute of TechnologyPhD in Electrical Engineering and Computer Science

From the biography.

  1. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Bowen Jing. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  2. 84% of people shaping AI with recorded undergraduate and doctoral schools changed institutions for their doctorateIncludes Bowen Jing. 84% of people shaping AI with recorded undergraduate and doctoral schools changed institutions for their doctorate. Across 2,116 people with both an undergraduate degree and a doctorate recorded, we trace which undergraduate schools feed which doctoral programs, how often students stay at the same school, and how paths differ by birth-country region.
  3. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Massachusetts Institute of Technology. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  4. 20% of people at companies who shape AI also hold a university role, led by Google and Stanford UniversityIncludes Stanford University. 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.

Sources and credits

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  1. Bowen Jing bjing2016.github.io. Checked 22 October 2026.
  2. Learning from Protein Structure with Geometric Vector Perceptrons arxiv.org. Checked 22 October 2026.
  3. Announcing the NeurIPS 2021 Award Recipients blog.neurips.cc. Checked 22 October 2026.
  4. ATOM3D: Tasks On Molecules in Three Dimensions arxiv.org. Checked 22 October 2026.
  5. Torsional Diffusion for Molecular Conformer Generation proceedings.neurips.cc. Checked 22 October 2026.
  6. DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking arxiv.org. Checked 22 October 2026.
  7. AlphaFold Meets Flow Matching for Generating Protein Ensembles arxiv.org. Checked 22 October 2026.
  8. ProtComposer: Compositional Protein Structure Generation with 3D Ellipsoids proceedings.iclr.cc. Checked 22 October 2026.
  9. SwitchCraft: A Programmatic Framework for Designing State-Switching Proteins arxiv.org. Checked 22 October 2026.
  10. Bowen Jing, PhD - Divergence Labs | Antibody Engineering & Therapeutics US Speaker aqmen365.com. Checked 22 October 2026.