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Short course on Convex Optimization and Applications, 21, 22, 23, 27 March
Lecture 1: Convex Optimization - From Real-Time Embedded to Large-Scale Distributed

Convex optimization has emerged as a useful tool for applications that include data analysis and model fitting, resource allocation, engineering design, network design and optimization, finance, and control and signal processing. After an overview, the talk will focus on two extremes: real-time embedded convex optimization, and distributed convex optimization. Code generation can be used to generate extremely efficient and reliable solvers for small problems, that can execute in milliseconds or microseconds, and are ideal for embedding in real-time systems. At the other extreme, we describe methods for large-scale distributed optimization, which coordinate many solvers to solve enormous problems.
Based on joint work by: Stephen Boyd, Jacob Mattingley, Neal Parikh, Eric Chu, Borja Pelleato, and Jon Eckstein.

Published recordings: On-demand video.
Type of Seminar:
IfA Seminar
Prof. Stephen Boyd
Electrical Engineering, Information Systems Laboratory, Stanford University
Mar 21, 2012   16:15

ETF E 1, Sternwartstr. 7
Contact Person:

John Lygeros
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Biographical Sketch:
Stephen P. Boyd is the Samsung Professor of Engineering, and Professor of Electrical Engineering in the Information Systems Laboratory at Stanford University. He also has a courtesy appointment in the Department of Management Science and Engineering, and is member of the Institute for Computational and Mathematical Engineering. His current research focus is on convex optimization applications in control, signal processing, and circuit design. Stephen P. Boyd received an AB degree in Mathematics, summa cum laude, from Harvard University in 1980, and a PhD in EECS from U. C. Berkeley in 1985. In 1985 he joined the faculty of Stanford’s Electrical Engineering Department. He has held visiting professor positions at Katholieke University (Leuven), McGill University (Montreal), Ecole Polytechnique Federale (Lausanne), Qinghua University (Beijing), Universite Paul Sabatier (Toulouse), Royal Institute of Technology (Stockholm), Kyoto University, Harbin Institute of Technology, NYU, and MIT. He holds an honorary doctorate from the Royal Institute of Technology (KTH), Stockholm. Stephen P. Boyd is the author of many research articles and three books: Linear Controller Design: Limits of Performance (with Craig Barratt, 1991), Linear Matrix Inequalities in System and Control Theory (with L. El Ghaoui, E. Feron, and V. Balakrishnan, 1994), and Convex Optimization (with Lieven Vandenberghe, 2004). His group has produced several open source tools, including CVX (with Michael Grant), a widely used parser-solver for convex optimization. Stephen P. Boyd has received many awards and honors for his research in control systems engineering and optimization, including an ONR Young Investigator Award and a Presidential Young Investigator Award. In 1992 he received the AACC Donald P. Eckman Award, which is given annually for the greatest contribution to the field of control engineering by someone under the age of 35. In 1993 he was elected Distinguished Lecturer of the IEEE Control Systems Society, and in 1999, he was elected Fellow of the IEEE, with citation: “For contributions to the design and analysis of control systems using convex optimization based CAD tools.” He has been invited to deliver more than 50 plenary and keynote lectures at major conferences in both control and optimization.