Xin Wang
Postdoctoral Fellow

Dr. Xin Wang works at the interface of experimental electrocatalysis and machine learning. She conducted wet-lab synthesis and characterization of electrocatalysts, collecting and curating data from both low-throughput, manually performed experiments and high-throughput automated workflows. Her work applied deep learning models to guide catalyst design, synthesis and performance prediction, bridging experimental chemistry and data-driven discovery in energy research.

Xin received her Bachelor’s degree in Chemical Engineering from Zhejiang University with Honors from Chu Kochen College, where she worked on gas-responsive star polymers as catalyst carriers. She earned her Ph.D. in Chemical Engineering from Cornell University with Prof. Nicholas Abbott, focusing on the design of functional soft materials. She was later awarded the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship at Cornell, through which she steered her research toward AI for electrochemistry in collaboration with Professors Héctor Abruña, Peter Frazier and Song Lin.