PeopleofSuperintelligence

Researcher

Alex Hernandez-Garcia

Also known as Alex Hernández-García

Alex Hernandez-Garcia is a machine-learning researcher whose work uses GFlowNets and active learning for scientific discovery. He earned bachelor's and master's degrees at the University Carlos III of Madrid and completed a PhD at Osnabrück on data augmentation for vision models. At Mila, he worked with Yoshua Bengio and David Rolnick, co-organized AI research events and coauthored work on biological sequence design and multi-fidelity molecular search. Since 2025, he is an assistant professor at Université de Montréal's DIRO and a core academic member at Mila, where he works on machine learning for climate and health. In 2026, he led GuideBench, an open-source clinical-guideline evaluation framework, and coauthored S3-GFN for synthesizable molecule generation.

Links
Google Scholar, X and GitHub

Timeline

  1. 2016–2020

    A PhD in Osnabrück

    He begins a PhD with Peter König at the University of Osnabrück in 2016 and defends it at the Institute of Cognitive Science in 2020. His dissertation, Data augmentation and image understanding, studies data augmentation as an inductive bias for vision models. He earns bachelor's and master's degrees at the University Carlos III of Madrid and completes research internships at Cambridge with Tim Kietzmann and at Amsterdam's Spinoza Center for Neuroimaging with Serge Dumoulin.

  2. 2020–2022

    Postdoctoral work at Mila

    In December 2020, he joins Mila as a postdoctoral researcher with Yoshua Bengio and David Rolnick. He serves as the elected postdoctoral Mila Lab Representative in 2021–2022.

  3. 2021–2022

    Organizing AI research events

    At NeurIPS 2021, he co-organizes a workshop on pre-registration in machine learning. In 2022, he co-organizes the AI Helps Ukraine charity conference.

  4. 2022

    Biological sequence design with GFlowNets

    In 2022, he coauthors Biological Sequence Design with GFlowNets, an active-learning method that uses GFlowNets to propose diverse and informative biological sequence candidates.

  5. 2023–2024

    Multi-fidelity active learning

    In 2023, he coauthors Multi-Fidelity Active Learning with GFlowNets, which searches molecular discovery tasks with lower-cost approximations of expensive objectives to find diverse, high-scoring candidates. Transactions on Machine Learning Research publishes the paper in 2024.

  6. Since 2025

    Assistant professor at Montréal

    He starts as an assistant professor at Université de Montréal's DIRO and a core academic member of Mila in early 2025. His machine-learning research supports scientific discoveries related to climate and health.

  7. 2026

    GuideBench for clinical guidelines

    In 2026, he leads GuideBench, an open-source evaluation framework for clinical guideline reasoning.

  8. 2026

    Synthesizable molecules with S3-GFN

    In 2026, he coauthors S3-GFN, a sequence-based GFlowNet that uses soft regularization and molecular priors to generate synthesizable molecules with high rewards.

Career

  1. Since 2021MilaPostdoctoral Researcher
  2. NowUniversité de MontréalAssistant Professor
  3. University of CambridgeResearch Intern
  4. Spinoza Center for NeuroimagingResearch Intern

Education

  1. 2020University of OsnabrückPhD
  2. Universidad Carlos III de MadridBachelor's degree

From the biography.

  1. The median h-index is 48 at universities and 14 at frontier AI labsIncludes Université de Montréal. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  2. 20% of people at companies who shape AI also hold a university role, led by Google and Stanford UniversityIncludes Université de Montréal. 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. Universities (31%) and startups and other companies (25%) employ the largest shares of 2020–2026 entrantsIncludes Mila. Among 819 people whose first recorded role started in 2020–2026 and who have a known current organization, 60% work in commercial sectors (25% at startups and other companies, 23% at frontier labs and 13% at big tech, with 9 in two), and 31% work at universities, compared with 66% for earlier entrants.
  4. Companies supply the most prior-work hires at 7 of the 9 frontier AI labsIncludes Mila. Our estimates of the organizations where 550 people worked directly before joining 9 frontier AI labs across 620 career transitions, comparing the main feeder organizations per lab.

Colleagues

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

Sources and credits

Photo: We have no published photo of Alex Hernandez-Garcia yet. Send us a free-licensed photo.

  1. Home | Alex Hernandez-Garcia alexhernandezgarcia.com. Checked 21 October 2026.
  2. Data augmentation and image understanding arxiv.org. Checked 21 October 2026.
  3. About me | Alex Hernandez-Garcia alexhernandezgarcia.com. Checked 21 October 2026.
  4. Biological Sequence Design with GFlowNets proceedings.mlr.press. Checked 21 October 2026.
  5. Multi-Fidelity Active Learning with GFlowNets arxiv.org. Checked 21 October 2026.
  6. Multi-Disciplinary Approaches to AI and Sustainability | Events - Concordia University concordia.ca. Checked 21 October 2026.
  7. Alex HERNANDEZ-GARCIA - Département d'informatique et de recherche opérationnelle - Université de Montréal diro.umontreal.ca. Checked 21 October 2026.
  8. Synthesizable Molecular Generation via Soft-constrained GFlowNets with Rich Chemical Priors arxiv.org. Checked 21 October 2026.