PeopleofSuperintelligence

Researcher

Gerrit Großmann

Gerrit Großmann is a computer scientist whose research links network science and machine learning to interacting systems, molecular graphs and events in space and time. He earned computer-science degrees at Saarland University and completed a doctorate on stochastic spreading across networks. His work includes a 2021 network study of COVID-19, GINA for hidden-graph inference, and 2025 papers on molecular diffusion and spatiotemporal point processes. Since 2026, he is a postdoctoral researcher in CISPA's Relational Machine Learning Lab, in collaboration with HIPS.

Timeline

  1. 2015–2018

    Computer science at Saarland

    He earns a BSc in computer science at Saarland University in 2015 and an MSc there in 2018.

  2. 2019–2022

    A PhD on network spreading

    He completes a PhD in computer science with Saarland University's Modeling and Simulation group in 2022; his dissertation is titled “Stochastic Spreading on Complex Networks.”

  3. 2021

    A COVID-19 network study

    In 2021, he coauthors a PLOS ONE study that uses stochastic simulations and contact networks to examine how connectivity and individual viral-load variation shape COVID-19 spread.

  4. 2023

    GINA infers hidden networks

    In 2023, he coauthors “Unsupervised Relational Inference Using Masked Reconstruction,” which introduces GINA to infer hidden interaction graphs from observations of interacting systems.

  5. 2023–2026

    Leading a DFKI team

    From 2023 to 2026, he serves as a Senior Researcher in DFKI's Neuro-mechanistic Modeling department and leads the Spatio-temporal Modeling and Forecasting team in its Data Science and its Applications group. His projects include neuro-symbolic guidance for diffusion models and semi-supervised learning on metabolic networks.

  6. 2025

    Diffusion for molecular graphs

    In 2025, he coauthors “Exploring Molecule Generation Using Latent Space Graph Diffusion,” comparing denoising diffusion, flow matching and heat-dissipation models across graph and E(3)-equivariant graph neural network architectures.

  7. 2025

    Neural spatiotemporal point processes

    In 2025, he coauthors “Neural Spatiotemporal Point Processes: Trends and Challenges,” a review that categorizes methods, unifies design choices and identifies open challenges for events in continuous space and time.

  8. Since 2026

    Postdoctoral researcher at CISPA

    Since 2026, he is a postdoctoral researcher at CISPA in the Relational Machine Learning Lab, in collaboration with the Helmholtz Institute for Pharmaceutical Research Saarland (HIPS).

Career

  1. Since 2026CISPA Helmholtz Center for Information SecurityPostdoctoral researcher
  2. 2023–2026DFKISenior Researcher
  3. 2023–2026Data Science and its Applications GroupTeam Lead

Education

  1. 2022Saarland UniversityPhD in computer science
  2. 2018Saarland UniversityMSc in computer science
  3. 2015Saarland UniversityBSc in computer science

From the biography.

  1. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes CISPA Helmholtz Center for Information Security. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  2. Nonprofit roles are 2.3 times as common in AI safetyIncludes DFKI. We estimate where people focused on safety, alignment and evaluation work. Nonprofit roles appear for 25.1% of safety people with known affiliations, compared with 11.0% in other areas.
  3. The top 10 organizations employed 22% of people shaping AI in 2025: 51% of company researchers and 21% of university researchersIncludes DFKI. We estimate the share of people shaping AI who worked at the top 10 organizations each year from 1955 to 2025, comparing concentration across companies, universities, and institutes and labs.
  4. The United States employs an estimated 48% of people shaping AIIncludes DFKI. We estimate where the people shaping AI work today, how universities, companies and research institutes split across countries, and how country shares have changed since the 1960s.

Colleagues

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

Sources and credits

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

  1. Gerrit Großmann | Data Science and its Applications dsa.dfki.de. Checked 22 October 2026.
  2. Gerrit Großmann gerritgrossmann.de. Checked 22 October 2026.
  3. Gerrit Großmann - Modeling and Simulation mosi.uni-saarland.de. Checked 22 October 2026.
  4. Heterogeneity matters: Contact structure and individual variation shape epidemic dynamics journals.plos.org. Checked 22 October 2026.
  5. GINA: Neural Graph Inference From Independent Snapshots of Interacting Systems github.com. Checked 22 October 2026.
  6. Exploring Molecule Generation Using Latent Space Graph Diffusion arxiv.org. Checked 22 October 2026.
  7. Neural Spatiotemporal Point Processes: Trends and Challenges arxiv.org. Checked 22 October 2026.
  8. Relational ML - Team relationalml.github.io. Checked 22 October 2026.