CBE Seminar: “From Molecules to Supply Chains: Transforming Data to Decisions using Geometry, Optimization, and Machine Learning” (Victor Zavala, University of Wisconsin-Madison)
April 23, 2025 at 3:30 PM - 4:30 PM
Abstract:
We discuss how geometry, optimization, and machine learning are key technologies that are revolutionizing the way we think about data and the way we transform data into actionable models and decisions. Specifically, we explain how complex data (e.g., text, molecules, time series, images/video, supply chain flows) can be represented as geometrical objects and how this facilitates the interpretation and extraction of useful information from data. We also discuss how extracted information can be mapped into decisions using optimization and machine learning models. We illustrate how to use these powerful math tools in innovative ways for analyzing complex datasets arising in molecular dynamics simulation, microscopy, chemical processes, and supply chains. Specifically, we show that these tools can help link the microstructure of soft gels to their rheological properties, can help analyze complex responses of liquid crystals from video data, and can help detect faults and optimize large-scale systems.
Victor Zavala
Baldovin-DaPra Professor of Chemical and Biological Engineering
Victor M. Zavala is the Baldovin-DaPra Professor in the Department of Chemical and Biological Engineering at the University of Wisconsin-Madison and a senior computational mathematician in the Mathematics and Computer Science Division at Argonne National Laboratory. He holds a B.Sc. degree from Universidad Iberoamericana and a Ph.D. degree from Carnegie Mellon University, both in chemical engineering. He is an associate editor for ACS-I&ECR and is on the editorial board of the journals Mathematical Programming Computation and Computers & Chemical Engineering. He is a recipient of NSF and DOE Early Career awards and of the Presidential Early Career Award forScienti sts and Engineers (PECASE). His research interests include data science, control, and optimization and applications to chemical, energy, and environmental systems.