Professor Victor Zavala, Department of Chemical and Biological Engineering, University of Wisconsin-Madison, WI, USA
Tuesday, April 26 and Wednesday, April 27
8:30 a.m. – 5:00 p.m.
Ibn Sina (bldg. 3), room 5220
To register for the course, please email sri.uq@kaust.edu.sa and include your name, institution and email address.
Summary of topics covered:
- Formulations of stochastic programming, including classical two-stage and multi-stage formulations, problems with probabilistic constraints and coherent risk measures.
- Application areas such as electrical and natural gas systems, energy storage technologies and combined heat and power systems with tight water constraints.
- Scalable algorithmic approaches for both continuous and mixed-integer formulations.
- Software tools amenable for high-performance computing environments.
Biography
Victor M. Zavala is the Richard H. Soit assistant professor in the Department of Chemical and Biological Engineering at the University of Wisconsin-Madison. Before joining UW-Madison, he was a computational mathematician in the Mathematics and Computer Science Division at Argonne National Laboratory. He received his B.Sc. degree from Universidad Iberoamericana (2003) and his Ph.D. degree from Carnegie Mellon University (2008), both in chemical engineering.
He is currently a recipient of a Department of Energy Early Career Award under which he develops scalable optimization algorithms. He is also a technical editor of the Mathematical Programming Computation journal. His research interests are in the areas of mathematical modeling of energy systems, high-performance computing, stochastic optimization and predictive control.
For more information, please visit:
https://sri-uq.kaust.edu.sa/Pages/Home.aspx.
Organizers:
Omar Knio
Deputy Director, Center for Uncertainty Quantification in Computational Science and Engineering
Professor, Computer, Electrical and Mathematical Science and Engineering Division, KAUST
Ricardo Lima
Research Scientist, Center for Uncertainty Quantification in Computational Science and Engineering
Computer, Electrical and Mathematical Science and Engineering Division, KAUST