Feng is a Scientist developing frontier AI models for structural biology, with a focus on steering structure predictors toward experimental data and identifying model failure modes. He earned his B.S. in Physics from Nanjing University and his M.S. and Ph.D. in Quantitative and Systems Biology from UC Merced. Before his current role, he was a postdoctoral fellow at Lawrence Berkeley National Laboratory’s SIBYLS Beamline, where he developed methods for modeling flexible proteins and dynamic ensembles.