Andrew Allman is an assistant professor in the Department of Chemical Engineering. He received his Ph.D. in chemical engineering in 2018 from the University of Minnesota with a thesis entitled “Enabling distributed renewable energy and chemical production through process systems engineering” under the guidance of Professor Prodromos Daoutidis. He received a B.S. with high honors in chemical engineering in 2013 from Penn State University. His research interests include developing theory and methods for the optimal design, control, planning, and scheduling of chemical and energy systems. He is particularly interested in applications that support sustainable water and energy usage and in decision making over multiple time scales.
Professor Allman’s research team focuses on identifying and exploiting the structure and sparsity inherent in the mathematical models underlying chemical, energy, and biological systems to enable computationally efficient decision making. Current theoretical areas of interest include (1) identifying easy-to-solve subproblems within large, complex optimization problems, (2) developing new solution approaches which better exploit a given problem’s structure, (3) enhancing data-driven decision-making methods through a priori dimensionality reduction in data collection, and (4) reducing the complexity of many-objective optimization problems by identifying subsets of objectives which have the strongest tradeoffs.
Professor Allman’s Scopus page