Cheng Zeng

Hi! I am a postdoctoral fellow working at the Instutite for Experiential AI and Roux institute of Northeastern University, mentored by Prof. Nathan Post and Prof. Jack Lesko. I am interested in solving complex engineering problems with machine learning, physical simulations and numerical methods. My research interests spans a multitude of topics including materials design, machine learning, electrochemistry, computational catalysis, corrosion protection and additive manufacturing. Prior to joining Roux, I received a PhD in Engineering at Brown University. En route to my PhD degree, I also received a secondary Master’s degree in Data Science via Brown’s Open Graduate Education Program. At Brown, I worked at the Catalyst Design Lab under the direction of Andrew Peterson. My PhD research focused on machine learning potentials and force–displacement phenomenological models for rational catalyst design. A key highlight of my work is that a combination of simulation techniques—including machine learning potential, the phenomenological model, a geometric descriptor and a microkinetic analysis—generates trends of surface catalytic activity of nanoparticle electrocatalysts in various sizes and alloy compositions. Prior to Brown, I got a Bachelor and Master in Materials Science and Engineering from Tsinghua University. At Tsinghua, I worked with Yunhan Ling on oxide films resistant to hydrogen permeation.