Data and Computational Engineering
CBE researchers are international leaders in computer modeling and analytics. Since the 1980s, we have been pioneers in bringing molecular simulations and electronic-structure modeling into chemical and biomolecular engineering, and this activity has broadened and deepened through ground-breaking research in theory, modeling, data science, applications and bioinformatics. We have discovered how Alzheimer's-related amyloid plaques form, parsed the cellular diversity of the brain using next-generation single-cell transcriptomics and bioinformatics, revealed how cellulose pyrolyzes through elementary reactions into bio-oil, and what molecular-scale steps are used by homogeneous catalysis to manufacture polymers and chemicals. We are increasingly using machine learning to design new materials and mixtures that will give desired properties, to uncover the mechanisms of aging and of intracellular signal transduction, and to unravel composition measurements of complicated mixtures, also drawing from data sources like our high-throughput computer imaging and our two-dimensional gas chromatography. We are also developing advanced control and optimization algorithms, driven by data science techniques and inherent problem structures, for challenging problems in the contemporary, broadly defined process systems engineering. Among our strengths for creating these advances are our rich collaborations within the department, the university, and around the world, and access to world-class high-performance-computing resources.
Prof. Crook
Developing new biological engineering methods in yeast and bacteria to advance human health and sustainability
Prof. Genzer
Using organic films to form polymer-nanoparticle composites by controlling the molecular parameters of the underlying films
Prof. Hall
Applying molecular thermodynamics and computer simulation to model self assembly of biological molecules and soft materials
Prof. Haugh
Investigating chemical reaction networks that are used for integrating information and prompting decision making
Prof. Keung
Developing molecular technologies to expand and unlock new ways to control, understand, and harness chromatin
Prof. San Miguel
Using engineering and systems approaches to study biological processes in the model organism Caenorhabditis elegans
Prof. Santiso
Using modern molecular simulation methods, machine learning tools, and metahuristic algorithms to discover new materials
Prof. Spontak
Focusing on the design, characterization, and modeling through the use of optical, electron, x-ray, and probe microscopies
Prof. Tang
Developing data-driven, structured control and optimization methods for complex decision making in process systems
Prof. Westmoreland
Focusing on reaction kinetics, applying computational quantum chemistry to complement their experimental research