Abstract: Combinatorial problems are ubiquitous across diverse fields in the sciences and industry. Despite rapid advances in computational power, most problems of interest stubbornly remain intractable and approximate solutions are typically employed. This presentation will introduce our emerging research for optimally solving combinatorial problems using a unique combination of linear programming and AI. We’ve developed methods for genetic and real-valued data and applied our methods to several phenotypes, including Alzheimer disease.
Speaker’s Bio: Dr. Sharlee Climer is an Assistant Professor in the Department of Computer Science at the University of Missouri – St. Louis and is also a faculty member of the Center for Neurodynamics and the Hope Center for Neurological Disorders. Her current research focuses the development of approximate and exact methods for identifying combinatorial patterns in big data, with a focus on genetic patterns associated with complex diseases.
Last Updated: July 2, 2021 - 8:52 am