Stephen P. Boyd
homepage:http://www.stanford.edu/~boyd/
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Description

Stephen P. Boyd is the Samsung Professor of Engineering, and Professor of Electrical Engineering in the Information Systems Laboratory at Stanford University. His current research focus is on convex optimization applications in control, signal processing, and circuit design.

Professor 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, and Harbin Institute of Technology. He holds an honorary doctorate from Royal Institute of Technology (KTH), Stockholm.

Professor 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).

Professor Boyd has received many awards and honors for his research in control systems engineering and optimization, including an ONR Young Investigator Award, a Presidential Young Investigator Award, and an IBM faculty development 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 30 plenary and keynote lectures at major conferences in both control and optimization.

In addition to teaching large graduate courses on Linear Dynamical Systems, Nonlinear Feedback Systems, and Convex Optimization, Professor Boyd has regularly taught introductory undergraduate Electrical Engineering courses on Circuits, Signals and Systems, Digital Signal Processing, and Automatic Control. In 1994 he received the Perrin Award for Outstanding Undergraduate Teaching in the School of Engineering, and in 1991, an ASSU Graduate Teaching Award. In 2003, he received the AACC Ragazzini Education award, for contributions to control education, with citation: “For excellence in classroom teaching, textbook and monograph preparation, and undergraduate and graduate mentoring of students in the area of systems, control, and optimization.


Lectures:

keynote
flag Convex Optimization with Abstract Linear Operators
as author at  International Conference on Computer Vision (ICCV) 2015, Santiago,
444 views
  invited talk
flag Domain Specific Languages for Convex Optimization
as author at  International Workshop on Advances in Regularization, Optimization, Kernel Methods and Support Vector Machines (ROKS): theory and applications, Leuven 2013,
430 views
invited talk
flag Alternating Direction Method of Multipliers
as author at  Optimization for Machine Learning,
7900 views
  lecture
flag Lecture 18: Announcements
as author at  Stanford Engineering Everywhere EE364B - Convex Optimization II,
56 views
lecture
flag Lecture 17: Stochastic Model Predictive Control
as author at  Stanford Engineering Everywhere EE364B - Convex Optimization II,
334 views
  lecture
flag Lecture 16: Model Predictive Control
as author at  Stanford Engineering Everywhere EE364B - Convex Optimization II,
911 views
lecture
flag Lecture 15: Recap: Example: Minimum Cardinality Problem
as author at  Stanford Engineering Everywhere EE364B - Convex Optimization II,
136 views
  lecture
flag Lecture 14: Methods (Truncated Newton Method)
as author at  Stanford Engineering Everywhere EE364B - Convex Optimization II,
115 views
lecture
flag Lecture 13: Recap: Conjugate Gradient Method
as author at  Stanford Engineering Everywhere EE364B - Convex Optimization II,
381 views
  lecture
flag Lecture 12: Recap: 'Difference Of Convex' Programming
as author at  Stanford Engineering Everywhere EE364B - Convex Optimization II,
261 views
lecture
flag Lecture 11: Sequential Convex Programming
as author at  Stanford Engineering Everywhere EE364B - Convex Optimization II,
204 views
  lecture
flag Lecture 10: Decomposition Applications
as author at  Stanford Engineering Everywhere EE364B - Convex Optimization II,
95 views
lecture
flag Lecture 9: Comments: Latex Typesetting Style
as author at  Stanford Engineering Everywhere EE364B - Convex Optimization II,
557 views
  lecture
flag Lecture 8: Recap: Ellipsoid Method
as author at  Stanford Engineering Everywhere EE364B - Convex Optimization II,
143 views
lecture
flag Lecture 7: Example: Piecewise Linear Minimization
as author at  Stanford Engineering Everywhere EE364B - Convex Optimization II,
201 views
  lecture
flag Lecture 6: Addendum: Hit-And-Run CG Algorithm
as author at  Stanford Engineering Everywhere EE364B - Convex Optimization II,
87 views
lecture
flag Lecture 5: Stochastic Programming
as author at  Stanford Engineering Everywhere EE364B - Convex Optimization II,
958 views
  lecture
flag Lecture 4: Project Subgradient For Dual Problem
as author at  Stanford Engineering Everywhere EE364B - Convex Optimization II,
120 views
lecture
flag Lecture 3: Convergence Proof
as author at  Stanford Engineering Everywhere EE364B - Convex Optimization II,
88 views
  lecture
flag Lecture 2: Recap: Subgradients
as author at  Stanford Engineering Everywhere EE364B - Convex Optimization II,
198 views
lecture
flag Lecture 1: Course Logistics
as author at  Stanford Engineering Everywhere EE364B - Convex Optimization II,
581 views
  event
flag Stanford Engineering Everywhere EE364B - Convex Optimization II
as author at  Stanford Engineering Everywhere EE364B - Convex Optimization II,
lecture
flag Lecture 19: Interior-Point Methods (Cont.)
as author at  Stanford Engineering Everywhere EE364A - Convex Optimization I,
227 views
  lecture
flag Lecture 18: Logarithmic Barrier
as author at  Stanford Engineering Everywhere EE364A - Convex Optimization I,
174 views
lecture
flag Lecture 17: Newton's Method (Cont.)
as author at  Stanford Engineering Everywhere EE364A - Convex Optimization I,
187 views
  lecture
flag Lecture 15: Algorithm Section Of The Course
as author at  Stanford Engineering Everywhere EE364A - Convex Optimization I,
141 views
lecture
flag Lecture 14: LU Factorization (Cont.)
as author at  Stanford Engineering Everywhere EE364A - Convex Optimization I,
225 views
  lecture
flag Lecture 13: Linear Discrimination (Cont.)
as author at  Stanford Engineering Everywhere EE364A - Convex Optimization I,
113 views
lecture
flag Lecture 12: Continue On Experiment Design
as author at  Stanford Engineering Everywhere EE364A - Convex Optimization I,
360 views
  lecture
flag Lecture 11: Statistical Estimation
as author at  Stanford Engineering Everywhere EE364A - Convex Optimization I,
1253 views
lecture
flag Lecture 10: Applications Section Of The Course
as author at  Stanford Engineering Everywhere EE364A - Convex Optimization I,
153 views
  lecture
flag Lecture 9: Complementary Slackness
as author at  Stanford Engineering Everywhere EE364A - Convex Optimization I,
558 views
lecture
flag Lecture 8: Lagrangian
as author at  Stanford Engineering Everywhere EE364A - Convex Optimization I,
841 views
  lecture
flag Lecture 7: Generalized Inequality Constraints
as author at  Stanford Engineering Everywhere EE364A - Convex Optimization I,
453 views
lecture
flag Lecture 6: (Generalized) Linear-Fractional Program
as author at  Stanford Engineering Everywhere EE364A - Convex Optimization I,
413 views
  lecture
flag Lecture 5: Optimal And Locally Optimal Points
as author at  Stanford Engineering Everywhere EE364A - Convex Optimization I,
271 views
lecture
flag Lecture 4: Vector Composition
as author at  Stanford Engineering Everywhere EE364A - Convex Optimization I,
298 views
  lecture
flag Lecture 3: Logistics
as author at  Stanford Engineering Everywhere EE364A - Convex Optimization I,
630 views
lecture
flag Lecture 1: Introduction to Convex Optimization I
as author at  Stanford Engineering Everywhere EE364A - Convex Optimization I,
2736 views
  event
flag Stanford Engineering Everywhere EE364A - Convex Optimization I
as author at  Stanford Engineering Everywhere EE364A - Convex Optimization I,
lecture
flag Lecture 20: Continuous-Time Reachability
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
55 views
  lecture
flag Lecture 19: Reachability
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
47 views
lecture
flag Lecture 18: Sensitivity Of Linear Equations To Data Error
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
61 views
  lecture
flag Lecture 17: Gain Of A Matrix In A Direction
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
57 views
lecture
flag Lecture 16: RC Circuit (Example)
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
418 views
  lecture
flag Lecture 15: DC Or Static Gain Matrix
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
114 views
lecture
flag Lecture 14: Jordan Canonical Form
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
275 views
  lecture
flag Lecture 13: Markov Chain (Example)
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
lecture
flag Lecture 12: Time Transfer Property
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
86 views
  lecture
flag Lecture 11: Solution Via Laplace Transform And Matrix Exponential
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
319 views
lecture
flag Lecture 10: Examples Of Autonomous Linear Dynamical Systems
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
192 views
  lecture
flag Lecture 9: Least-Norm Solution
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
105 views
lecture
flag Lecture 8: Multi-Objective Least-Squares
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
154 views
  lecture
flag Lecture 7: Least-Squares Polynomial Fitting
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
292 views
lecture
flag Lecture 6: Least-Squares
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
393 views
  lecture
flag Lecture 5: Orthonormal Set Of Vectors
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
234 views
lecture
flag Lecture 4: Nullspace Of A Matrix(Continued)
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
180 views
  lecture
flag Lecture 3: Linearization (Continued)
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
264 views
lecture
flag Lecture 2: Linear Functions (Continued)
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
335 views
  lecture
flag Lecture 1: Overview Of Linear Dynamical Systems
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
1337 views
event
flag Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems
as author at  Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,