The Gray lab creates algorithms for protein engineering. Pictured: A deep learning model for antibody structure prediction from sequence. Credit: Jeff Ruffolo.

Artificial intelligence (AI), machine learning (ML), modeling, and simulation have the potential to transform and accelerate the discovery, development and manufacturability of systems transcending length- and time-scales. The Department of Chemical and Biomolecular Engineering at has a remarkable breadth and depth of talent in these areas, with five faculty members deeply engaged in developing new algorithms to open new frontiers in chemical engineering.

Our work spans the challenges of the 21st century: From climate change and sustainable energy to health and therapeutics, to flexible electronic materials and molecular design.

We offer an educational program of courses tailored to Chemical and Biomolecular Engineering students, from ranging from foundational courses, such as Software Carpentry, to high-level courses, such as Modern Data Analysis and Machine Learning.

Primary Faculty

Michael Bevan
Brandon Bukowski
Paulette Clancy
Jeffrey Gray
Yannis Kevrekidis