Bill Basener is a Professor at the School of Data Science with a joint appointment in the Department of Systems and Information Engineering. He has authored research publications in machine learning, signal processing, image processing, dynamical systems, game theory, ecological economics, evolutionary genetics, and other applied mathematical fields, as well as a textbook on applied topology and multiple patents.

The methods and software he developed for processing images in hyperspectral imaging have become the gold-standard in the field, used for processing millions of images by dozens of organizations. The Basener-Ross model he developed for modeling ecological collapse has been used for studying ancient civilizations. His textbook, Topology and Its Applications, was one of the first textbooks in the field of applied topology, and covered diverse applications in cosmology, chaos theory, condensed matter physics, protein folding, computer graphics, and robot coordination. He invented the topological anomaly detection, gradient flow clustering, hierarchical material identification, and object-based identification algorithms in image processing. This technology has been used in disaster relief efforts across the world.

Prior to joining the School of Data Science in 2014, Basener was an Emeritus Professor at the Rochester Institute of Technology of Mathematical Sciences. He is also the founder and president of two data analytics software companies, Geospatial Technology Associates and Spectral Solutions. Basener holds a PH.D. in Mathematics from Boston University and a B.S. in Mathematics from Marist College.

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Bill Basener

Hyperspectral Imaging: Q&A with Bill Basener

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