Dr. Rothberg has served in senior leadership positions in optimization software companies for more than twenty years. Prior to his role as Gurobi CEO, Dr. Rothberg held the Gurobi COO position since co-founding Gurobi in 2008, and prior to that he led the ILOG CPLEX team. Dr. Edward Rothberg has a BS in Mathematical and Computational Science from Stanford University, and an MS and PhD in Computer Science, also from Stanford University. Dr. Rothberg has published numerous papers in the fields of linear algebra, parallel computing, and mathematical programming. He is one of the world's leading experts in sparse Cholesky factorization and computational linear, integer, and quadratic programming.

Edward Rothberg is CEO and Co-Founder of Gurobi Optimization, which produces the world's fastest mathematical optimization solver. This is a question that -- as the CEO of a mathematical optimization software company -- I get asked all the time. Although it seems like a simple question, it's actually quite difficult to come up with a concise, coherent answer. Indeed, mathematical optimization and machine learning are two tools that at first glance -- like scissors and pliers -- may seem to have a lot in common. When you look closely at their fundamental features and actual applications, however, you'll see some important differences.