Abstract

While not as well-known as more publicized technologies such as machine learning, artificial intelligence and quantum computing, mathematical optimization is heavily used by numerous industries to operate more efficiently.  Advances over the last 60 years in both the algorithms and the computers on which they are implemented have made the technology increasingly useful to a growing number of industries. This growth has resulted in increasing demand for employees with mathematical optimization skills.This presentation will examine the different types of mathematical optimization problems currently being solved and the diverse types of industrial applications that make use of the technology.  We will also consider the different types of available career paths.  Finally, we will explore connections between mathematical optimization and machine learning, artificial intelligence and quantum computing.

Bio

Dr. Ed Klotz is a Mathematical Optimization Specialist at Gurobi Optimization with over 30 years of experience in the mathematical optimization software industry. Over the course of his career, he has worked with a wide array of customers to help them solve some of world’s most challenging mathematical optimization problems. Dr. Klotz works closely with Gurobi users to support them in implementing and utilizing mathematical optimization in their organizations. He also interacts heavily with the R&D team based on his experiences with the customers.  Before joining Gurobi in June of 2020, he had a similar role as part of the CPLEX R&D team, which he joined in 1991. He has extensive knowledge in linear programming, integer programming, and numerical linear algebra for finite precision computing.  He has presented at numerous conferences, workshops and web seminars and published papers on mathematical optimization. His interests are on all aspects of mathematical programming with a primary interest on research that can have an impact on mathematical programming software. He obtained a BA in Math and Economics from Oberlin College and a PhD in Operations Research from Stanford University.