I’ve been awarded a 2026 AI in Science Schmidt Fellowship Seed Fund ($33K, as PI) for the project “AI-Guided Discovery of PFAS-Selective Membrane Interfaces: From Autonomous Design to Experimental Validation.”

This project is an end-to-end test of the autonomous discovery stack we have been building: hypothesis generation with DToR, candidate screening through T³-style device digital twins, atomistic sanity checks with RAPIDS, and finally wet-lab synthesis and electrochemical validation of the designed membrane interfaces.

PFAS (“forever chemicals”) removal has everything that makes the data-scarce, unbenchmarked regime hard: multi-component interfaces, expensive experiments, no public dataset to lean on. Whether the loop survives contact with a real membrane problem is what this project is set up to find out.

Thanks to Schmidt Sciences and the UChicago AI in Science program for the support.