Naim Matasci

Research data infrastructure that lets AI-driven discovery compound across projects.

I build the computational platforms that research organizations run on — the orchestration layers, systems of record and data pipelines that let machine learning methods accumulate value across projects instead of being rebuilt for each one. I have done this twice: for the plant sciences, as Scientific Lead of the NSF's iPlant Collaborative (later CyVerse), and for cancer research.

I have been at the Ellison Medical Institute in Los Angeles since 2014, in progressively senior roles across data management, analytics, bioinformatics and computational biology, and am now Senior Director, Applied AI Research. My group works across AI-driven molecular design, computational pathology, and the clinical and genomic data platform underneath both. I am also a Visiting Scholar at Harvey Mudd College.

Recent work includes AI methods for designing molecules against targets that conventional approaches reach poorly, and foundation-model studies predicting treatment response from breast cancer histopathology.

My doctoral work was in evolutionary genetics at the Max Planck Institute for Evolutionary Anthropology in Leipzig, with Svante Pääbo.

Selected work

Selected talks and posters

Service

Served on the FASEB Generative AI Task Force (2024) and the FASEB DataWorks! Advisory Committee (2022–24). External scientific advisor to Project EAGER, an NIH-funded undergraduate genomics training program, and a member of Harvey Mudd College's Innovation Accelerator Laboratory for Emerging Health Technology.

Documents

Elsewhere