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.
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keynote
Convex Optimization with Abstract Linear Operators
as author at International Conference on Computer Vision (ICCV) 2015, Santiago,
6179 views
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invited talk
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,
5642 views
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invited talk
Alternating Direction Method of Multipliers
as author at Optimization for Machine Learning,
50474 views
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lecture
Lecture 18: Announcements
as author at Stanford Engineering Everywhere EE364B - Convex Optimization II,
2583 views
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lecture
Lecture 17: Stochastic Model Predictive Control
as author at Stanford Engineering Everywhere EE364B - Convex Optimization II,
4025 views
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lecture
Lecture 16: Model Predictive Control
as author at Stanford Engineering Everywhere EE364B - Convex Optimization II,
6635 views
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lecture
Lecture 15: Recap: Example: Minimum Cardinality Problem
as author at Stanford Engineering Everywhere EE364B - Convex Optimization II,
3236 views
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lecture
Lecture 14: Methods (Truncated Newton Method)
as author at Stanford Engineering Everywhere EE364B - Convex Optimization II,
2700 views
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lecture
Lecture 13: Recap: Conjugate Gradient Method
as author at Stanford Engineering Everywhere EE364B - Convex Optimization II,
3847 views
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lecture
Lecture 12: Recap: 'Difference Of Convex' Programming
as author at Stanford Engineering Everywhere EE364B - Convex Optimization II,
3847 views
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lecture
Lecture 11: Sequential Convex Programming
as author at Stanford Engineering Everywhere EE364B - Convex Optimization II,
3579 views
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lecture
Lecture 10: Decomposition Applications
as author at Stanford Engineering Everywhere EE364B - Convex Optimization II,
2826 views
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lecture
Lecture 9: Comments: Latex Typesetting Style
as author at Stanford Engineering Everywhere EE364B - Convex Optimization II,
4556 views
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lecture
Lecture 8: Recap: Ellipsoid Method
as author at Stanford Engineering Everywhere EE364B - Convex Optimization II,
3054 views
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lecture
Lecture 7: Example: Piecewise Linear Minimization
as author at Stanford Engineering Everywhere EE364B - Convex Optimization II,
3468 views
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lecture
Lecture 6: Addendum: Hit-And-Run CG Algorithm
as author at Stanford Engineering Everywhere EE364B - Convex Optimization II,
2736 views
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lecture
Lecture 5: Stochastic Programming
as author at Stanford Engineering Everywhere EE364B - Convex Optimization II,
6616 views
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lecture
Lecture 4: Project Subgradient For Dual Problem
as author at Stanford Engineering Everywhere EE364B - Convex Optimization II,
2985 views
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lecture
Lecture 3: Convergence Proof
as author at Stanford Engineering Everywhere EE364B - Convex Optimization II,
2552 views
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lecture
Lecture 2: Recap: Subgradients
as author at Stanford Engineering Everywhere EE364B - Convex Optimization II,
3464 views
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lecture
Lecture 1: Course Logistics
as author at Stanford Engineering Everywhere EE364B - Convex Optimization II,
5330 views
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event
Stanford Engineering Everywhere EE364B - Convex Optimization II
as author at Stanford Engineering Everywhere EE364B - Convex Optimization II,
8857 views
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lecture
Lecture 19: Interior-Point Methods (Cont.)
as author at Stanford Engineering Everywhere EE364A - Convex Optimization I,
3243 views
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lecture
Lecture 18: Logarithmic Barrier
as author at Stanford Engineering Everywhere EE364A - Convex Optimization I,
2920 views
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lecture
Lecture 17: Newton's Method (Cont.)
as author at Stanford Engineering Everywhere EE364A - Convex Optimization I,
3041 views
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lecture
Lecture 15: Algorithm Section Of The Course
as author at Stanford Engineering Everywhere EE364A - Convex Optimization I,
3111 views
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lecture
Lecture 14: LU Factorization (Cont.)
as author at Stanford Engineering Everywhere EE364A - Convex Optimization I,
3536 views
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lecture
Lecture 13: Linear Discrimination (Cont.)
as author at Stanford Engineering Everywhere EE364A - Convex Optimization I,
3006 views
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lecture
Lecture 12: Continue On Experiment Design
as author at Stanford Engineering Everywhere EE364A - Convex Optimization I,
3913 views
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lecture
Lecture 11: Statistical Estimation
as author at Stanford Engineering Everywhere EE364A - Convex Optimization I,
7328 views
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lecture
Lecture 10: Applications Section Of The Course
as author at Stanford Engineering Everywhere EE364A - Convex Optimization I,
3122 views
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lecture
Lecture 9: Complementary Slackness
as author at Stanford Engineering Everywhere EE364A - Convex Optimization I,
3894 views
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lecture
Lecture 8: Lagrangian
as author at Stanford Engineering Everywhere EE364A - Convex Optimization I,
5534 views
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lecture
Lecture 7: Generalized Inequality Constraints
as author at Stanford Engineering Everywhere EE364A - Convex Optimization I,
5177 views
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lecture
Lecture 6: (Generalized) Linear-Fractional Program
as author at Stanford Engineering Everywhere EE364A - Convex Optimization I,
4543 views
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lecture
Lecture 5: Optimal And Locally Optimal Points
as author at Stanford Engineering Everywhere EE364A - Convex Optimization I,
3691 views
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lecture
Lecture 4: Vector Composition
as author at Stanford Engineering Everywhere EE364A - Convex Optimization I,
3635 views
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lecture
Lecture 3: Logistics
as author at Stanford Engineering Everywhere EE364A - Convex Optimization I,
5334 views
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lecture
Lecture 1: Introduction to Convex Optimization I
as author at Stanford Engineering Everywhere EE364A - Convex Optimization I,
14776 views
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event
Stanford Engineering Everywhere EE364A - Convex Optimization I
as author at Stanford Engineering Everywhere EE364A - Convex Optimization I,
21860 views
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lecture
Lecture 20: Continuous-Time Reachability
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
2688 views
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lecture
Lecture 19: Reachability
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
2558 views
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lecture
Lecture 18: Sensitivity Of Linear Equations To Data Error
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
2632 views
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lecture
Lecture 17: Gain Of A Matrix In A Direction
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
2588 views
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lecture
Lecture 16: RC Circuit (Example)
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
3940 views
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lecture
Lecture 15: DC Or Static Gain Matrix
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
3214 views
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lecture
Lecture 14: Jordan Canonical Form
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
3834 views
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lecture
Lecture 13: Markov Chain (Example)
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
3614 views
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lecture
Lecture 12: Time Transfer Property
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
2788 views
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lecture
Lecture 11: Solution Via Laplace Transform And Matrix Exponential
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
3821 views
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lecture
Lecture 10: Examples Of Autonomous Linear Dynamical Systems
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
3577 views
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lecture
Lecture 9: Least-Norm Solution
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
3217 views
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lecture
Lecture 8: Multi-Objective Least-Squares
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
3227 views
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lecture
Lecture 7: Least-Squares Polynomial Fitting
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
3706 views
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lecture
Lecture 6: Least-Squares
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
4460 views
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lecture
Lecture 5: Orthonormal Set Of Vectors
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
3413 views
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lecture
Lecture 4: Nullspace Of A Matrix(Continued)
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
4109 views
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lecture
Lecture 3: Linearization (Continued)
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
3429 views
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lecture
Lecture 2: Linear Functions (Continued)
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
3886 views
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lecture
Lecture 1: Overview Of Linear Dynamical Systems
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
8436 views
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event
Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems
as author at Stanford Engineering Everywhere EE263 - Introduction to Linear Dynamical Systems,
17796 views
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Springer,
