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Chemical & Biological Engineering Research

Rendering of Molecules

Theory, Data Science and Systems

We develop and apply theoretical and computational methods that span all length scales, such as quantum chemical calculations to predict reaction mechanisms, molecular simulations to study solvent-mediated processes, computational fluid dynamics to model complex flows, theories to understand principles of self-organizing systems, and numerical methods to optimize processes and supply chains. Machine learning methods are being broadly developed and applied to complement these techniques. This research area is cross-cutting and benefits from extensive collaboration with experimentalists in the department.

Representative Topics

Machine learning, computational chemistry, molecular simulations, process modeling and optimization, computational fluid dynamics.


Core faculty: Avraamidou, Cersonsky, Graham, Klingenberg, Mavrikakis, Swaney, Van Lehn, Yin, Zavala

Affiliate faculty: Raman, Romero, Spagnolie, Venturelli

Centers, Consortia and Institutes

Major research centers that collaborate with or include CBE faculty:

CBE-led centers: