Jon’s research focus is on nonlinear discrete optimization (NDO). Many practical engineering problems have physical aspects which are naturally modeled through smooth nonlinear functions, as well as design aspects which are often modeled with discrete variables. Research in NDO seeks to marry diverse techniques from classical areas of optimization, for example methods for smooth nonlinear optimization and methods for integer linear programming, with the idea of successfully attacking natural NDO models for practical engineering problems. On particular area of applied interest is environmental monitoring and the framework of maximum-entropy sampling.
COntact
Location
Ann Arbor
Methodologies
Graph-Based Methods / Information Theory / Networks / Optimization
Applications
Economics, Finance and Business / Engineering / Physical Science /