PeopleofSuperintelligence

Researcher

Martin Vögele

Martin Vögele is a computational biophysicist who combines molecular simulation with machine learning to study biological systems and predict how drug candidates behave. After physics degrees at Konstanz and Stuttgart, he earned a doctorate at Goethe University Frankfurt in 2019 with research at the Max Planck Institute of Biophysics. As a postdoctoral researcher in Ron Dror's lab at Stanford from 2019 to 2022, he coauthored ATOM3D, a set of benchmark datasets for machine learning on three-dimensional molecular structure that won a Best Paper Award at the NeurIPS 2021 Datasets and Benchmarks Track. He also coauthored PENSA, software for comparing biomolecular conformational ensembles, published in 2025. Since 2022, he is a Senior Scientist at Schrödinger, where he works on predicting ligand efficacy.

Now at
Schrodinger
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Timeline

  1. 2011–2014

    Physics at Konstanz and Stuttgart

    He earns a B.Sc. in physics at the University of Konstanz in 2011 and an M.Sc. in physics at the University of Stuttgart in 2014.

  2. 2014–2019

    Doctoral research with Gerhard Hummer

    From 2014 to 2019, he is a doctoral researcher in Gerhard Hummer's Department of Theoretical Biophysics at the Max Planck Institute of Biophysics in Frankfurt. He helps found the regional student chapter of the German Physical Society and serves for three years as the institute's PhD representative.

  3. 2019

    Doctorate from Goethe University

    He earns his PhD from Goethe University in 2019, based on research at the Max Planck Institute of Biophysics, where he develops theoretical frameworks and molecular simulations for the physics of lipid membranes. His thesis wins the Walter Greiner Award for the best doctoral thesis of 2019/2020 in the university's physics department.

  4. 2019–2022

    Postdoc in the Dror Lab

    In 2019, he joins Stanford University's Department of Computer Science as a postdoctoral researcher with Ron Dror, supported by an EMBO long-term fellowship from July 2019 to June 2021. He uses supercomputer simulations to study membrane receptor signaling and develops and benchmarks machine learning approaches that predict the behavior of drug candidates.

  5. 2021

    ATOM3D wins a NeurIPS award

    He coauthors ATOM3D with Raphael Townshend, Ron Dror and others: a collection of benchmark datasets spanning several classes of biomolecules, released with an open-source atom3d Python package. The paper compares three-dimensional convolutional networks, graph networks and equivariant networks across its tasks. It wins a Best Paper Award at the NeurIPS 2021 Datasets and Benchmarks Track, announced in November 2021.

  6. 2022–2025

    Euclidean transformers and PENSA

    In 2022, he coauthors 'Euclidean Transformers for Macromolecular Structures: Lessons Learned' with Ron Dror, Raphael Townshend and colleagues for ICML Computational Biology 2022. The PENSA software he coauthors for comparing biomolecular conformational ensembles from molecular simulations, generative AI models or structural biology experiments is published in the Journal of Chemical Physics in 2025.

  7. Since 2022

    Senior scientist at Schrödinger

    He joins Schrödinger in 2022 as a Senior Scientist in the Department of Life Science Software. His first Schrödinger publication, in November 2023, asks whether a receptor's functional response is determined by the thermodynamics of ligand binding, answers yes, and uses the result to predict ligand efficacy. In September 2026, he and colleagues show how to apply FEP-based efficacy prediction to ion channels.

Career

  1. Since 2022SchrodingerSenior Scientist
  2. 2019–2022Stanford UniversityPostdoctoral researcher
  3. 2014–2019Max Planck SocietyDoctoral researcher

Education

  1. 2019Goethe University FrankfurtPhD
  2. 2014University of StuttgartM.Sc. in physics
  3. 2011University of KonstanzB.Sc. in physics

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 Martin Vögele. 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. 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.
  3. Google has the highest combined h-index among AI organizationsIncludes Max Planck Society. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.
  4. Google had the most people shaping AI every year from 2014 to 2025Includes Stanford University. Our estimates of which organizations employed the most people shaping AI each year from 1955 to 2025, tracing the shift from university labs to companies.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

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  1. CV - Martin Vögele / Personal Website martinvoegele.github.io. Checked 21 October 2026.
  2. Martin Vögele | 500 Queer Scientists 500queerscientists.com. Checked 21 October 2026.
  3. About Me - Martin Vögele / Personal Website martinvoegele.github.io. Checked 21 October 2026.
  4. NeurIPS 2021 Awards neurips.cc. Checked 21 October 2026.
  5. Announcing the NeurIPS 2021 Award Recipients – NeurIPS Blog blog.neurips.cc. Checked 21 October 2026.
  6. [2012.04035] ATOM3D: Tasks On Molecules in Three Dimensions arxiv.org. Checked 21 October 2026.
  7. Publications - Martin Vögele / Personal Website martinvoegele.github.io. Checked 21 October 2026.