Arthur E. Bryson | |
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Born | October 7, 1925 |
Nationality | American |
Alma mater | California Institute of Technology |
Awards |
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Scientific career | |
Fields | Control theory |
Thesis | An Interferometric Wind Tunnel Study of Transonic Flow past Wedge and Circular Arcs [1] |
Doctoral advisor | Hans Wolfgang Liepmann [1] |
Doctoral students |
Arthur Earl Bryson Jr. (born October 7, 1925) [2] is the Paul Pigott Professor of Engineering Emeritus at Stanford University and the "father of modern optimal control theory".[ citation needed ] With Henry J. Kelley, he also pioneered an early version of the backpropagation procedure, [3] [4] [5] now widely used for machine learning and artificial neural networks.
He was a member of the U.S. Navy V-12 program at Iowa State College, and received his B.S. in aeronautical engineering there in 1946. [6] He earned his Ph.D. from the California Institute of Technology, graduating in 1951. His thesis An Interferometric Wind Tunnel Study of Transonic Flow past Wedge and Circular Arcs was advised by Hans W. Liepmann.
Bryson was the Ph.D. advisor to the Harvard control theorist Yu-Chi Ho.
In 1970, Bryson was elected a member of the National Academy of Engineering for contributions to engineering education and imaginative application of modern statistical methods to engineering optimization.
He was awarded membership into the National Academy of Engineering in 1970 and the National Academy of Sciences in 1973. He was awarded the John R. Ragazzini Award in 1982 from the American Automatic Control Council, the IEEE Control Systems Science and Engineering Award in 1984, [7] [8] the Richard E. Bellman Control Heritage Award in 1990 from the American Automatic Control Council [9] and the Daniel Guggenheim Medal in 2009.
In machine learning, a neural network is a model inspired by the structure and function of biological neural networks in animal brains.
In machine learning, backpropagation is a gradient estimation method commonly used for training neural networks to compute the network parameter updates.
Petar V. Kokotovic is professor emeritus in the College of Engineering at the University of California, Santa Barbara, USA. He has made contributions in the areas of adaptive control, singular perturbation techniques, and nonlinear control especially the backstepping stabilization method.
Eduardo Daniel Sontag is an Argentine-American mathematician, and distinguished university professor at Northeastern University, who works in the fields control theory, dynamical systems, systems molecular biology, cancer and immunology, theoretical computer science, neural networks, and computational biology.
A native of Terre Haute, Indiana, Stuart E. Dreyfus is professor emeritus at University of California, Berkeley in the Industrial Engineering and Operations Research Department. While at the Rand Corporation he was a programmer of the JOHNNIAC computer. While at Rand he coauthored Applied Dynamic Programming with Richard Bellman. Following that work, he was encouraged to pursue a Ph.D. which he completed in applied mathematics at Harvard University in 1964, on the calculus of variations. In 1962, Dreyfus simplified the Dynamic Programming-based derivation of backpropagation using only the chain rule. He also coauthored Mind Over Machine with his brother Hubert Dreyfus in 1986.
The Richard E. Bellman Control Heritage Award is an annual award given by the American Automatic Control Council (AACC) for achievements in control theory, named after the applied mathematician Richard E. Bellman. The award is given for "distinguished career contributions to the theory or applications of automatic control", and it is the "highest recognition of professional achievement for U.S. control systems engineers and scientists".
Yu-Chi "Larry" Ho is a Chinese-American mathematician, control theorist, and a professor at the School of Engineering and Applied Sciences, Harvard University.
Kumpati S. Narendra is an American control theorist, who currently holds the Harold W. Cheel Professorship of Electrical Engineering at Yale University. He received the Richard E. Bellman Control Heritage Award in 2003. He is noted "for pioneering contributions to stability theory, adaptive and learning systems theory." He is also well recognized for his research work towards learning including Neural Networks and Learning Automata.
Mustafa Tamer Başar is a control and game theorist who is the Swanlund Endowed Chair and Center for Advanced Study Professor of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign, USA. He is also the Director of the Center for Advanced Study.
Harold Joseph Kushner is an American applied mathematician and a Professor Emeritus of Applied Mathematics at Brown University. He is known for his work on the theory of stochastic stability, the theory of non-linear filtering, and for the development of numerical methods for stochastic control problems such as the Markov chain approximation method. He is commonly cited as the first person to study Bayesian optimization, based on work he published in 1964.
John Valentine Breakwell was a noted American control theorist and a Professor of Astronautics at Stanford University. He is remembered for his contributions to the "science and applications of astrodynamics, for discovery of flight-trajectory optimization, and for outstanding academic service." He was elected to the National Academy of Engineering in 1981 and a recipient of the Richard E. Bellman Control Heritage Award in 1983.
Yann André LeCun is a French-American computer scientist working primarily in the fields of machine learning, computer vision, mobile robotics and computational neuroscience. He is the Silver Professor of the Courant Institute of Mathematical Sciences at New York University and Vice-President, Chief AI Scientist at Meta.
Dimitri Panteli Bertsekas is an applied mathematician, electrical engineer, and computer scientist, a McAfee Professor at the Department of Electrical Engineering and Computer Science in School of Engineering at the Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, and also a Fulton Professor of Computational Decision Making at Arizona State University, Tempe.
Mathukumalli VidyasagarFRS is a leading control theorist and a Fellow of Royal Society. He is currently a Distinguished Professor in Electrical Engineering at IIT Hyderabad. Previously he was the Cecil & Ida Green (II) Chair of Systems Biology Science at the University of Texas at Dallas. Prior to that he was an executive vice-president at Tata Consultancy Services (TCS) where he headed the Advanced Technology Center. Earlier, he was the director of Centre for Artificial Intelligence and Robotics (CAIR), a DRDO defence lab in Bangalore. He is the son of eminent mathematician M V Subbarao.
Pravin Pratap Varaiya was Nortel Networks Distinguished Professor in the Department of Electrical Engineering at the University of California, Berkeley.
Henry J. Kelley (1926-1988) was Christopher C. Kraft Professor of Aerospace and Ocean Engineering at the Virginia Polytechnic Institute. He produced major contributions to control theory, especially in aeronautical engineering and flight optimization.
Andrzej Cichocki is a Polish computer scientist, electrical engineer and a professor at the Systems Research Institute of Polish Academy of Science, Warsaw, Poland and a visiting professor in several universities and research institutes, especially Riken AIP, Japan. He is most noted for his learning algorithms for Signal separation (BSS), Independent Component Analysis (ICA), Non-negative matrix factorization (NMF), tensor decomposition, Deep (Multilayer) Matrix Factorizations for ICA, NMF, PCA, neural networks for optimization and signal processing, Tensor network for Machine Learning and Big Data, and brain–computer interfaces. He is the author of several monographs/books and more than 500 scientific peer-reviewed articles.
In machine learning, hyperparameter optimization or tuning is the problem of choosing a set of optimal hyperparameters for a learning algorithm. A hyperparameter is a parameter whose value is used to control the learning process.
Multi-task optimization is a paradigm in the optimization literature that focuses on solving multiple self-contained tasks simultaneously. The paradigm has been inspired by the well-established concepts of transfer learning and multi-task learning in predictive analytics.
Frank L. Lewis is an American electrical engineer, academic and researcher. He is a professor of electrical engineering, Moncrief-O’Donnell Endowed Chair, and head of Advanced Controls and Sensors Group at The University of Texas at Arlington (UTA). He is a member of UTA Academy of Distinguished Teachers and a charter member of UTA Academy of Distinguished Scholars.