Group Leader
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Phil Rauscher, Ph.D.
Assistant Professor, Chemical and Biomolecular Engineering
p.rauscher@nyu.edu
Phil is a theoretical and computational physicist with a background spanning academia and industry. He obtained his B.S. in Physics from Emory University (2013) before joining IBM as a software consultant. After completing his Ph.D. in Molecular Engineering at the University of Chicago (2020), he joined Syensqo (then Solvay) as a research scientist. He has been at NYU Tandon since 2025. In his free time, he enjoys playing with his two children, cooking, chess, rugby, and shot put.
Graduate Students
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Anas Aqil
Anas Aqil is a Ph.D. student in Chemical Engineering at NYU Tandon. He applies machine learning to large, high-dimensional electrochemical reaction datasets to build predictive models and uncover patterns that can guide experiments and system design. He is especially interested in bridging rigorous chemical engineering fundamentals with modern data-driven methods. His work sits at the intersection of electrochemistry, data science, and chemical reaction engineering. Prior to his doctoral studies, he worked as a Technical Services Engineer in the petroleum refining industry, specializing in process simulation, design, and optimization.
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Rosa Zhang
Rosa is a Ph.D. student in the Department of Chemical and Biomolecular Engineering, co-advised by Prof. Justin Bui and Prof. Phillip Rauscher. She earned her B.S. in Chemical Engineering from the University of California, Berkeley in 2022, where she worked at Berkeley National Lab on porous electrode modeling for PEM fuel cells. She then spent three years as a software engineer, building in-house computational tools for a gene-editing start-up. Rosa is now combining her computational background and interest in electrochemistry to build physics-based machine learning models for electrochemical systems. Rosa is from California, where she grew up playing all types of water sports. Outside of research, she enjoys plotting her next surf trip, playing underwater hockey, and exploring New York City.
Postdoctoral Associates
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Adam Lahouari, Ph.D.
I am a computational chemist driven by two things. The first is application — exploring new molecules, new interactions, and new materials, and using simulation to understand behavior that isn't yet well characterized. I work mostly on molecular crystals, reactive surfaces, and hydrogen-bonded systems, with applications ranging from pharmaceutical polymorphs to battery electrolytes. The second is methodology: I like pushing existing methods further and building new ones, particularly machine-learned interatomic potentials and the automation needed to train and deploy them at scale. The problems I enjoy most sit where those two meet — where getting the science right requires improving the method first.