Braxton Osting is an Assistant Professor in the Department of Mathematics at the University of Utah. He has broad interests in analytical and computational methods for problems in applied mathematics, especially in partial differential equations, optimization and control, graph theory, and machine learning.
After attending the University of Washington for his undergraduate studies, Braxton earned a Ph.D. in Applied Mathematics at Columbia University under the guidance of Michael Weinstein and David Keyes. His doctoral thesis was entitled Spectral Optimization Problems Controlling Wave Phenomena. Before moving to Utah, he was an NSF Postdoctoral Fellow in the Department of Mathematics at the University of California, Los Angeles, where his postdoctoral mentor was Stan Osher.
In his free time, Braxton enjoys biking, skiing, running, and hiking.
- Waves, Spectral Theory, and Applications, September 10-11, 2015
- Graph Algorithms for Imaging and Networks, November 14, 2015
- Western States Mathematical Physics Meeting, February 15-16, 2016
- AMS Sectional Meeting, April 9-10, 2016
- PCMI Graduate Summer School on The Mathematics of Data, June 30 - July 20, 2016
- Optimal and Random Point Configurations, June 27-July 1, 2016
- IMA Thematic Year on Mathematics and Optics, September 1, 2016 - June 30, 2017