PeopleofSuperintelligence

Researcher

José Jiménez-Luna

José Jiménez-Luna is a researcher who applies machine learning to drug discovery and protein science. He grew up in Seville, studied statistics in Seville and Barcelona, and earned a PhD at Pompeu Fabra University in 2019, where his dissertation used convolutional neural networks on three-dimensional atomistic systems. He coauthored a 2020 review of explainable AI for drug discovery and a 2022 review of structure-based deep learning, as well as QMugs and BioEmu-1, which samples protein structure ensembles. As of October 2026, he is a Senior Researcher at Microsoft Research Cambridge, focused on explainable AI for drug discovery, quantum machine learning and structural biology.

Badges

Timeline

  1. By 2019

    Statistics and a Pompeu Fabra PhD

    Seville is where he grows up and pursues a BSc in statistics at the University of Seville; he interns at IMC with the aim of providing statistical technical support in social and demographic studies. In Barcelona, he pursues an MSc in Statistics and Operations Research at UPC, then completes a PhD in Gianni de Fabritiis’ biophysics laboratory at Pompeu Fabra University in 2019, with a dissertation on convolutional neural networks for three-dimensional atomistic systems.

  2. 2019

    DeltaDelta neural networks

    In 2019, he coauthors a study that uses deep 3D convolutional neural networks to rank congeneric molecule series for drug lead optimization.

  3. 2020

    Explaining AI for drug discovery

    With Francesca Grisoni and Gisbert Schneider, he publishes a 2020 review of explainable AI for drug discovery. The review surveys methods, applications, opportunities and challenges for AI in molecular science.

  4. 2021

    QMugs molecular dataset

    In 2021, he coauthors QMugs, an open dataset of quantum-mechanical properties for more than 665,000 biologically and pharmacologically relevant molecules from ChEMBL, with about two million conformers. The collection supports machine-learning studies of molecular properties.

  5. 2022

    Structure-based deep learning review

    In 2022, he coauthors a review with Rıza Özçelik, Derek van Tilborg and Francesca Grisoni on deep learning for structure-based drug discovery. It surveys key methods, opportunities, applications and challenges.

  6. February 2025

    Releasing BioEmu-1

    In February 2025, he coauthors Microsoft Research’s BioEmu-1 release, a generative deep-learning model that samples protein structure ensembles. It offers orders of magnitude greater computational efficiency than classical molecular-dynamics simulations.

  7. As of October 2026

    Senior researcher at Microsoft

    Before joining Microsoft Research, he works as a postdoctoral fellow in Gisbert Schneider’s molecular design laboratory at ETH Zurich, funded by Boehringer Ingelheim Pharma. As of October 2026, he is a Senior Researcher at Microsoft Research Cambridge, focused on explainable AI for drug discovery and its real-life applications, quantum machine learning and structural biology.

Career

  1. NowMicrosoft ResearchSenior Researcher
  2. IMCIntern
  3. ETH ZurichPostdoctoral Fellow

Education

  1. 2019Universitat Pompeu FabraPhD
  2. University of SevilleBSc in Statistics
  3. Polytechnic University of CataloniaMSc in Statistics and Operations Research

From the biography.

  1. 16% of AI career moves in the 2020s went from a university to a companyIncludes José Jiménez-Luna. We estimate that 16% of AI career moves in the 2020s went from a university to a company; 29% of moves starting at a university went to a company, and 76% ended the university role.
  2. Among employers with 30+ full-time cases, OpenAI leads primary technical role H-1B pay at $310,000, and Amazon, Google and Microsoft file 57% of all casesIncludes Microsoft. Across 440,669 certified US H-1B filings from 44 employers (FY2020–FY2026), OpenAI leads primary technical role base pay at $310,000 and xAI leads overall base pay at $290,000.
  3. Google had the most people shaping AI every year from 2014 to 2025Includes Microsoft. 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.
  4. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes Microsoft. 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.

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 José Jiménez-Luna yet. Send us a free-licensed photo.

  1. About me - José Jiménez-Luna josejimenezluna.github.io. Checked 21 October 2026.
  2. Jose Jimenez-Luna at Microsoft Research microsoft.com. Checked 21 October 2026.
  3. DeltaDelta neural networks for lead optimization of small molecule potency pmc.ncbi.nlm.nih.gov. Checked 21 October 2026.
  4. Drug discovery with explainable artificial intelligence arxiv.org. Checked 21 October 2026.
  5. QMugs: Quantum Mechanical Properties of Drug-like Molecules arxiv.org. Checked 21 October 2026.
  6. Structure-based drug discovery with deep learning arxiv.org. Checked 21 October 2026.
  7. Exploring the structural changes driving protein function with BioEmu-1 microsoft.com. Checked 21 October 2026.