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Stephen P. Boyd

From Wikipedia, the free encyclopedia
Stephen P. Boyd
Born
California, United States[1]
NationalityAmerican
Alma mater
Known forConvex optimization techniques[2]
Awards
Scientific career
Fields
InstitutionsStanford University
ThesisVolterra Series: Engineering Fundamentals (1985)
Doctoral advisor
Doctoral studentsMung Chiang

Stephen P. Boyd is an American professor and control theorist. He is the Samsung Professor of Engineering, Professor in Electrical Engineering, and professor by courtesy in Computer Science and Management Science & Engineering at Stanford University. He is also affiliated with Stanford's Institute for Computational and Mathematical Engineering (ICME).

In 2014, Boyd was elected a member of the National Academy of Engineering for contributions to engineering design and analysis via convex optimization.

Academic biography

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Education

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Boyd received an AB degree in mathematics, summa cum laude, from Harvard University in 1980,[3] and a PhD in electrical engineering and computer sciences from the University of California, Berkeley in 1985 under the supervision of Charles A. Desoer, S. Shankar Sastry and Leon Ong Chua. While at Berkeley, he was awarded a Hertz Fellowship (1982) and received the Hertz Thesis Prize (1985).[4][5] In 2006 he was awarded an honorary doctorate from the Royal Institute of Technology in Stockholm, Sweden,[3] and in 2017, from the Université catholique de Louvain in Belgium.[6]

Career

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Boyd joined the faculty of Stanford University's Electrical Engineering department in 1985.[3] He regularly teaches undergraduate courses in applied linear algebra and machine learning. During his time at Stanford, he has been recognized with several teaching awards, including the 2016 Walter J. Gores Award for excellence in teaching, the school's highest teaching honor.[7] He was awarded the 2017 IEEE James H. Mulligan Jr. Education Medal, in recognition of his efforts in education in the theory and application of optimization, which has sparked the writing of improved linear algebra and convex optimization textbooks.[8] He has served as director of Stanford's Information Systems Laboratory,[3] and as a visiting professor at universities including City University of Hong Kong, Massachusetts Institute of Technology, New York University, Royal Institute of Technology in Stockholm, and Katholieke Universiteit Leuven in Belgium.[9][10] While at Stanford, he has consulted with numerous Silicon Valley tech companies, and founded one. His groups' CVXGEN software is used in SpaceX's Falcon 9 and Falcon Heavy to guide their autonomous precision landing.[3][11]

Research

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Boyd's primary research interests are convex optimization, especially applications in control, signal processing, machine learning, and finance. His PhD dissertation was on Volterra series descriptions of nonlinear circuits and devices.[12] His primary focus then turned to automatic control systems, where he focused on applying convex optimization, specifically linear matrix inequalities (LMIs), to a variety of control system analysis and synthesis problems.[13]

With Craig Barratt, he authored Linear Controller Design: Limits of Performance in 1991.[14] In 1994, Boyd and Laurent El Ghaoui, Eric Feron, and Ragu Balakrishnan authored the book Linear Matrix Inequalities in System & Control Theory.[15] Around 1999, he and Lieven Vandenberghe developed a PhD-level course and wrote the book Convex Optimization to introduce and apply convex optimization to other fields.[13]

In 2005 he and Michael Grant developed the MATLAB open source software package CVX, which makes it easy to specify and solve convex optimization problems.[16] This work earned them the 2012 Beale-Orchard-Hays Prize for Excellence in Computational Mathematical Programming.[17] In 2012 he and Jacob Mattingley developed CVXGEN, which generates fast custom code for small, quadratic-programming-representable convex optimization problems, using an online interface. With minimal effort, it turns a mathematical problem description into a high-speed solver.[18]

Open-source software packages developed by his research group are widely used and include:

  • CVXPY,[19]
  • SCS, first-order primal-dual cone solver for large problems[20]
  • OSQP (with Oxford)[21]

Boyd is ranked top 10 scientist in the field of Engineering and Technology.[22]

Business and patents

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Boyd co-founded and served as chief scientist of analog synthesis and intellectual property provider Barcelona Design, from its 1999 founding until it folded in 2005.[23][24] He serves in an advisory capacity for BlackRock, an investment management corporation;[25] Petuum, a machine learning platform for artificial intelligence;[26] and H2O.ai, open source machine learning platform.[27] He is also a co-inventor on 11 patents.[28] On his personal website, which is visited more than 1.6 million times per year, he makes available papers, books, software, lecture notes and lecture videos.[5]

Awards and honors

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Bibliography

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References

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  1. ^ "Interview with Prof. Stephen Boyd: A Scholar with Entrepreneurship". CUHK. 26 Nov 2018. Retrieved 31 Dec 2021.
  2. ^ Stephen P. Boyd was elected in 2014 as a member of National Academy of Engineering in Electronics, Communication & Information Systems Engineering and Industrial, Manufacturing & Operational Systems Engineering for contributions to engineering design and analysis via convex optimization.
  3. ^ a b c d e f g h i Stephen P. Boyd – Biography, Stanford.edu, January 9, 2018.
  4. ^ Stephen Poythress Boyd at the Mathematics Genealogy Project
  5. ^ a b c d [1] Hertz Foundation.
  6. ^ DHC, uclouvain.be, May 18, 2017.
  7. ^ a b Kathleen J. Sullivan, "Stanford's 2016 Cuthbertson, Dinkelspiel and Gores awards honor faculty, staff and students," Stanford News, June 7, 2016.
  8. ^ a b "Stephen P. Boyd accepts the IEEE James H. Mulligan, Jr. Education Medal – Honors Ceremony 2017," IEEE.tv, June 2, 2017.
  9. ^ Stephen P. Boyd Executive Profile, Bloomberg.com. Accessed March 26, 2018.
  10. ^ Stephen Boyd Biography, sse.cuhk.edu.cn, 2017.
  11. ^ NAE, The Bridge, Autonomous Precision Landing of Space Rockets, December 19, 2016, Author: Lars Blackmore.
  12. ^ Stephen P. Boyd, Volterra Series, University of California, Berkeley, 1985.
  13. ^ a b c Kylie Jue, "Q&A: Professor Stephen Boyd talks election to National Academy of Engineering," Stanford Daily, February 24, 2014.
  14. ^ Linear Controller Design – Limits of Performance, Stanford.edu. Retrieved March 26, 2018.
  15. ^ Linear Matrix Inequalities in System and Control Theory, 1994.
  16. ^ Guang-Ren Duan, LMIs in Control Systems: Analysis, Design and Applications, Boca Raton, FL: Taylor & Francis Group, 2013, p. 86.
  17. ^ "CVX wins the Beale-Orchard-Hays prize!" CVX Research, August 29, 2012.
  18. ^ CVXGEN: Code Generation for Convex Optimization, cvxgen.com, December 4, 2013.
  19. ^ "Citing CVXPY" CVXPY, accessed 10/08/20.
  20. ^ "CSC Read Me", accessed 10/08/20.
  21. ^ "Citing OSQP", accessed 10/09/20.
  22. ^ "Research.com - Leading Academic Research Portal". Research.com. Retrieved 2022-03-30.
  23. ^ "Costello's analog automation pioneer, Barcelona, to fold," EE Times, March 4, 2005.
  24. ^ "Barcelona Design Unveils Revolutionary Analog Circuit Solution," Design & Reuse, April 8, 2002.
  25. ^ Robin Wigglesworth, "BlackRock bulks up research into artificial intelligence," Financial Times, February 19, 2018.
  26. ^ Aaron Aupperlee, "Pittsburgh AI company Petuum opens office in Silicon Valley," Pittsburgh Tribune-Review, February 20, 2018.
  27. ^ Wendy Wong, "Start Off 2017 with Our Stanford Advisors," h2o.ai, January 9, 2017.
  28. ^ Stephen P. Boyd, Justia Patents. Retrieved March 26, 2018.
  29. ^ Stephen P. Boyd, informs.org. Accessed March 26, 2018.
  30. ^ Stephen Boyd named as 2016 INFORMS Fellow, ee.stanford.edu, October 2016.
  31. ^ Sarah Zheng, "Bill Gates given one of China's highest academic honours," South China Morning Post, November 27, 2017.
  32. ^ "European Association for Signal Processing, Awards, Athanasios Papoulis" European Association for Signal Processing, accessed 10/08/20.
  33. ^ "IEEE CDC 2020", accessed 10/13/20.
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