Bio

A short bio you can use for talk announcements.

Kevin Jablonka develops the methodology for AI-driven materials discovery — AI that operates on what a chemist actually controls (recipes, conditions, processing, raw instrument data) and predicts the function they need to optimize, so the methods reach real laboratories. He directs an independent research group at the Helmholtz Institute for Polymers in Energy Applications (HIPOLE Jena) and Friedrich-Schiller University Jena, with 71 publications and over 4,800 citations growing roughly 1.7× year-over-year; 10 of 21 first/corresponding-author papers appear in Nature/Science-family journals or A* conference proceedings. His research is featured in Nature, Nature Reviews Materials, MIT Technology Review, and Chemistry World.

Kevin shapes the field’s infrastructure as well as its content. As Co-Speaker of the NFDI FAIRmat consortium in its second funding phase, he co-leads Germany’s national infrastructure for FAIR materials data; as Area Chair for NeurIPS 2026 and on the organizing committee of the 2027 Faraday Discussion on Digital Chemical Discovery, he helps foster the community and field. He directs over €4M in PI funding (Carl Zeiss Foundation, OpenPhilanthropy, Intel–Merck, Google, Helmholtz Foundation Model Initiative) and leads AI work in industrial research consortia with Sasol (Care-o-Sene Fischer–Tropsch catalysts) and Intel–Merck (MatAssist agentic material and process design). His group of 11 Ph.D. students and one postdoctoral researcher earned the “Best Research Environment” award from Die Junge Akademie and the Volkswagen Foundation, and group alumni have continued at Stanford and gathered internships in companies such as Lila and BASF. Kevin is a Google Research Scholar, an elected member of Die Junge Akademie | Mainz, a member of the Foresight Institute, and was a red teamer for OpenAI. He earned his Ph.D. at EPFL (Chorafas Foundation award, Top 8% Thesis Distinction) after the second-highest master’s GPA among all EPFL graduates and the best in chemistry.

Shorter version

Kevin Jablonka develops the methodology for AI-driven materials discovery and directs an independent research group at HIPOLE Jena and Friedrich-Schiller University Jena. 71 publications, ~4,800 citations growing ~1.7× year-over-year, €4M+ in PI funding. Co-Speaker of the NFDI FAIRmat consortium, Area Chair for NeurIPS 2026, and on the organizing committee of the 2027 Faraday Discussion on Digital Chemical Discovery.

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If you need a headshot, you can use one of these (photographer: Marina Romanova/HIPOLE Jena).

Short CV

Key Career Milestones

Jun 2023 - Present: Independent Research Group Leader (Tenure Track with right to award doctoral degrees)
CZS Research Group at HIPOLE Jena and Friedrich-Schiller University Jena

Jul 2024 - Dec 2025: Red Teamer (Independent Contractor)
OpenAI

Aug 2019 - Jun 2023: Ph.D. in Chemistry and Chemical Engineering
École polytechnique fédérale de Lausanne (EPFL), Switzerland
Dimitris N. Chorafas Foundation award for outstanding Ph.D. work
Doctoral program Top 8% Thesis Distinction

Sep 2017 - Jul 2019: MSc. in Chemistry (high distinction, 5.95/6.00)
École polytechnique fédérale de Lausanne (EPFL), Switzerland
2nd best GPA among all master graduates at EPFL, best GPA in chemistry

Oct 2014 - Aug 2017: BSc. in Chemistry (high distinction, 1.2/1.0)
Technical University of Munich, Germany

Academic Summary

Leadership

Founder and director of the LAMALab for AI-accelerated materials discovery. Co-Speaker of the NFDI FAIRmat consortium in its second funding phase, co-leading Germany’s national infrastructure for FAIR materials data and the area “Enabling Data-driven Science”. Co-Leader of WG3 (Multi-modal machine learning methods) in DAEMON COST Action. Area Chair for NeurIPS 2026 (also AI4Mat 2024 and ICLR AI4Mat 2025). Organizing committee of the 2027 Faraday Discussion on Digital Chemical Discovery. Initiator of CECAM flagship workshops (L2M3, MADICES) and recurring global LLM hackathons for materials science, resulting in publications with >40 co-authors.

Research Impact

71 publications; over 4,800 citations growing roughly 1.7× year-over-year. 10 of 21 first/corresponding-author papers (48%) in Nature/Science-family journals or A* conference proceedings, including Nature Chemistry (2), Nature Communications (2), Nature Computational Science, Nature Machine Intelligence, npj Computational Materials, Science Advances, and the NeurIPS main track. Research highlighted in Nature, Nature Reviews Materials, Materials Today, Chemistry World, MIT Technology Review, and RTS Radio Télévision Suisse. See Google Scholar.

Funding & Industrial Programs

Over €4M as PI from Carl Zeiss Foundation, OpenPhilanthropy, Intel–Merck, Google, and Helmholtz Foundation Model Initiative. Leads AI work in industrial research consortia: Care-o-Sene (Sasol-linked Fischer–Tropsch catalysts for sustainable aviation fuel) and MatAssist (Intel–Merck joint research center on agentic material and process design).

Teaching & Open Resources

Designed flipped-classroom ML courses for chemistry and materials students. Conceived the seminar Critical Aspects of AI, bringing ethics, governance, and risk into scientific AI practice. Open educational resources: online book on LLM data extraction methods, interactive web environments for spectroscopy teaching, and open ML book. Guest lecturer at international schools.

Group & Mentorship

Directs 11 Ph.D. students and one postdoctoral researcher (12 Ph.D. students from August 2026), with rotating master’s students, interns, and visiting students. Group received the “Best Research Environment” award by Die Junge Akademie and the Volkswagen Foundation. Group alumni have placed at Stanford and gather internships at startups such as Lila. Trained in scientific leadership by the Helmholtz Leadership Academy.

Public Impact

Featured on AI podcasts (e.g. from ARD). Speaker at Young Chemists Network of the German Chemical Society. Hands-on workshop organizer for international hackathons, workshops and conferences.

Selected Honors

  • Helmholtz AI Award for Best Digital Resource (ChemBench, 2025)
  • Google Research Scholar Award (2025)
  • “Best Research Environment” award by Die Junge Akademie and the Volkswagen Foundation (2025)
  • Finalist for “Rising Star in Computational Materials Science” (2025)
  • Member of the Foresight Institute (Berlin node, 2026)
  • Election into the Junge Akademie | Mainz (2025)
  • Dimitris N. Chorafas Foundation award for outstanding Ph.D. thesis (2023)
  • Member of the CAS FutureLeaders 2022 cohort
  • Alfred-Werner scholarship by the Swiss Chemical Society (2017)
  • Scholarship by the German scholarship foundation (Studienstiftung des Deutschen Volkes, 2015)