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Committee Chairs
Chair, WLA Prize Awards Committee
Chair, World Laureates Association
2006 Nobel Prize in Chemistry
Winzer Professor in Medicine, Stanford University
Major Awards and Honors:

1993, Member of National Academy of Sciences of the United States

1999, Fellow of the American Academy of Arts and Sciences

2001, Welch Awarder, the highest prize in the American chemical industry

2006, Nobel Prize in Chemistry

Education and Work Experience:

1972, Ph.D. from Stanford University.

1976-1978, Assistant Professor of the Department of Biological Chemistry of Harvard Medical School.

1978-Present, Professor of the Department of structural Biology, Stanford University School of Medicine.

Main Academic Achievements:

Professor Kornberg discovered that the nucleosome, the basic unit of chromosomal DNA organization in the eukaryotic nucleus. He and Prof. Yahli Lorch showed that the nucleosome on a promoter prevents the initiation of DNA transcription, establishing the role of the nucleosome as a gene repressor, fundamental to the new field of epigenetics. Professor Kornberg solved the threedimensional structure of RNA polymerase by, X-ray diffraction, both alone and in the form of an actively transcribing complex, containing gene DNA and product RNA. Professor Kornberg discovered the molecular basis for the regulation of transcription by gene activator and repressor proteins. His research laid a foundation for understanding the differentiation of stem cells and the mechanisms of human diseases and other important medical problems.

Chair, 2023 WLA Prize Selection Committee (Life Science or Medicine)
Vice Chair, World Laureates Association
Professor in University of California, Berkeley
Major Awards and Honors:

1992, Member of the United States National Academy of Sciences

2002, Albert Lasker Award in Basic Medical Research

2013, Foreign Associate, The Royal Society, London

2013, Nobel Prize in Physiology or Medicine

Education and Work Experience:

1975, PhD in Biochemistry, Stanford University School of Medicine

1989-Present, Professor, Department of Molecular and Cell Biology, University of California, Berkeley

1990-Present, Investigator, Howard Hughes Medical Institute

Main Academic Achievements:

Prof. Schekman began investigating networks of intracellular membranes associated with the vesicle transport of proteins in the yeast Saccharomyces cerevisiae at Berkeley. With the aid of others in his laboratory, he screened yeast for mutations that blocked the secretion of certain enzymes from cells. The work led to the discovery of membrane fusion regulator proteins encoded by SEC genes. In subsequent work Schekman and colleagues discovered that nearly two dozen genes play a role in vesicle transport. They characterized the function of each gene’s protein and elucidated the sequence in which the proteins act to effect transport. Schekman’s work also provided insight into mechanisms of vesicle budding and protein transport from the endoplasmic reticulum.

Michael I. JORDAN
Chair, 2023 WLA Prize Selection Committee (Computer Science or Mathematics)
Pehong Chen Distinguished Professor, Department of Electrical Engineering and Computer Sciences & Department of Statistics, University of California, Berkeley
Major Awards and Honors:

2009, ACM/AAAI Allen Newell Award

2010, Member, National Academy of Sciences

2010, Member, National Academy of Engineering

2020, John von Neumann Medal (Institute of Electrical and Electronics Engineers, IEEE)

2021, Ulf Grenander Prize in Stochastic Theory and Modeling (American Mathematical Society, AMS)

2022, WLA Prize in Computer Science or Mathematics

Education and Work Experience:

1985, PhD in Cognitive Science, University of California, San Diego

1998-present, Professor, Department of Electrical Engineering and Computer Sciences, Department of Statistics, University of California, Berkeley

2015-2017, Chair, Department of Statistics, University of California, Berkeley

2017-present, Professor, Department of Industrial Engineering and Operations Research, University of California

Main Academic Achievements:

Prof. Michael I. Jordan’s has made great contributions at the interface between computer science and statistics include the variational approach to statistical inference and learning, inference methods based on graphical models and Bayesian non-parametrics, and characterizations of tradeoffs between statistical risk and computational complexity. He has also worked at the interface between optimization and machine learning, where he is well-known for his development of continuous-time models of gradient-based optimization and sampling, and his work on distributed systems for optimization. He has built bridges between machine learning and control theory, contributing to the theory of reinforcement learning, learning-based model predictive control, and optimality principles for human motor control. He has also led the way in bringing microeconomic concepts into contact with machine learning, developing learning methods that incentivize learners to share data, showing how contract theory can be employed for statistical inference, and advancing the study of learning-based matching markets.

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