Many current products and systems employ sophisticated mathematical algorithms to automatically make complex decisions, or take action, in real-time. Examples include recommendation engines, search engines, spam filters, on-line advertising systems, fraud detection systems, automated trading engines, revenue management systems, supply chain systems, elecricity generator scheduling, flight management systems, and advanced engine controls. I’ll cover the basic ideas behind these and other applications, emphasizing the central role of mathematical optimization and the associated areas of machine learning and automatic control. The talk will be nontechnical, but the focus will be on understanding the central issues that come up across many applications, such as the development or learning of mathematical models, the role of uncertainty, the idea of feedback or recourse, and computational complexity.
Research Activities :
Convex optimization applications in control, signal processing, and circuit design
Honors and Awards :
- 2013: IEEE Field Award in Control Systems
- 2003: The AACC Ragazzini Education award
- 1992: AACC Donald P. Eckman Award