Organizing Committee Members

Emery Brown
enb@neurostat.mit.edu

Emery Brown is the Edward Hood Taplin Professor of Medical Engineering and Computational Neuroscience at MIT; the Warren M. Zapol Professor of Anaesthesia at Harvard Medical School; and a practicing anesthesiologist at Massachusetts General Hospital. Prof. Brown is an anesthesiologist-statistician whose experimental research has made important contributions to understanding how anesthetics act in the brain to create the states of general anesthesia. In his statistics research he has developed signal processing algorithms to study dynamic processes in neuroscience. Prof. Brown served on the NIH BRAIN Initiative Working Group. He is the recipient of an NIH Director’s Pioneer Award, an NIH Director’s Transformative Research Award, the Jerome Sacks Award from the National Institute of Statistical Science and a Guggenheim Fellowship. He is a fellow of the American Institute for Medical and Biological Engineering, the American Statistical Association, the American Association for the Advancement of Science, the IEEE, and the American Academy of Arts Sciences. Prof. Brown is a member of the Institute of Medicine, the National Academy of Sciences, and the National Academy of Engineering.

Munther Dahleh
dahleh@mit.edu

Munther Dahleh is acting director of the Engineering Systems Division (ESD) and director-designate of the new Institute for Data, Systems, and Society which focuses on addressing complex societal challenges using rigorous data-analytic tools. Prof. Dahleh joined LIDS as an assistant professor of EECS in 1987 and became a full professor in 1998. He spent the spring of 1993 as a visiting professor in the Department of Electrical Engineering, California Institute of Technology, and has held consulting positions with several companies in the U.S. and abroad. He is a distinguished scholar whose research record reflects diverse contributions ranging from robust control theory to the analysis and design of dynamic system over physical and information networks. His most recent work focuses on developing mathematical foundations for the analysis of fragility and cascaded failures as well as information propagation in networked systems, with applications in energy, transportation, finance, and social networks. 

Michael Jordan
jordan@cs.berkeley.edu
jordan@stat.berkeley.edu

Michael Jordan is the Pehong Chen Distinguished Professor in the Department of Electrical Engineering and Computer Science and the Department of Statistics at the University of California, Berkeley. His research in recent years has focused on Bayesian nonparametric analysis, probabilistic graphical models, spectral methods, kernel machines and applications to problems in signal processing, statistical genetics, computational biology, information retrieval and natural language processing. Prof. Jordan was elected a member of the National Academy of Sciences (NAS) and the National Academy of Engineering (NAE) in 2010, and of the American Academy of Arts and Sciences in 2011. He is a fellow of the American Association for the Advancement of Science (AAAS). He has been named a Neyman Lecturer and a Medallion Lecturer by Institute of Mathematical Statistics (IMS). He is a fellow of the IMS, IEEE, AAAI, and ASA.

Anna Mikusheva
amikushe@mit.edu

Anna Mikusheva is the Castle-Krob Career Development Associate Professor of Economics at MIT. Prof. Mikusheva received a PhD in economics from Harvard University (2007) and PhD in mathematics from Moscow State University (2001). She is a recipient of the 2012 Elaine Bennett Research Prize, a bi-annual prize from the American Economic Association established to recognize and honor outstanding reseach in any field of economics by a woman at the beginning of her career. She was also selected as a 2013 Sloan Research Fellow.

Speakers

Patrick Bajari
bajari@econ.umn.edu

Patrick Bajari is vice president and chief economist for Amazon. He earned his doctorate in economics in 1997 from the University of Minnesota where he specialized in applied econometrics and empirical industrial organization. He was a member of the economics faculty at Harvard, Stanford, Duke, and Minnesota, and is a research fellow at the National Bureau of Economic Research. Bajari worked for the Boston Consulting Group from 1999 to 2010 in pricing, providing applied econometric work to guide decision making in a variety of industries. He also worked as a consultant to the research departments for the Federal Reserve Banks of San Francisco and Minneapolis, and served as an antitrust expert witness. Bajari joined Amazon in 2010 where he reports to Jeff Wilke, the Senior Vice President for the North American Consumer Platform. He has used economic and econometric tools to build automated systems for pricing, forecasting, ordering, and marketing spend, in addition to providing applied econometric analysis on a host of other business problems.
 

Peter Bickel
bickel@stat.berkeley.edu

Peter Bickel is professor emeritus in the Department of Statistics at University of California, Berkeley. Prof. Bickel has been a leading figure in the field of statistics in the 43 years since he received his PhD in statistics at the age of 22. He has pioneered research in many statistical disciplines and has made fundamental contributions in many areas of statistics, including robust statistics, decision theory, semiparametric modeling, bootstrap, nonparametric modeling, machine learning, computational biology, and many other areas where statistics and quantitative approaches play an important role. He was awarded an honorary doctorate degree from Hebrew University, Jerusalem, in 1986. He is past president of the Bernoulli Society and of the Institute of Mathematical Statistics, a MacArthur Fellow, a COPSS prize winner, and a member of both the American Academy of Arts and Sciences and the National Academy of Sciences. He was also honored as the (UC-Berkeley) Chancellor's Distinguished Professor (1996-1999).

Andrew Gelman
gelman@stat.columbia.edu

Andrew Gelman is a professor of statistics and political science and director of the Applied Statistics Center at Columbia University. He has received the Outstanding Statistical Application award from the American Statistical Association, the award for best article published in the American Political Science Review, and the Council of Presidents of Statistical Societies award for outstanding contributions by a person under the age of 40. His books include Bayesian Data Analysis (with John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Don Rubin), Teaching Statistics: A Bag of Tricks (with Deb Nolan), Data Analysis Using Regression and Multilevel/Hierarchical Models (with Jennifer Hill), Red State, Blue State, Rich State, Poor State: Why Americans Vote the Way They Do (with David Park, Boris Shor, and Jeronimo Cortina), and A Quantitative Tour of the Social Sciences (co-edited with Jeronimo Cortina).

Lars Peter Hansen
lhansen@uchicago.edu

Lars Peter Hansen is the David Rockefeller Distinguished Service Professor in Economics, Statistics and the College and research director of the Becker Friedman Institute for Research in Economics at the University of Chicago. Prof. Hansen is a recipient of the 2013 Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel for his early research. He won the 2010 BBVA Foundation Frontiers of Knowledge Award in the Economics, Finance and Management "for making fundamental contributions to our understanding of how economic actors cope with risky and changing environments." In 2008, he was awarded the CME Group-MSRI Prize in Innovative Quantitative Applications. Prof. Hansen is one of two scholars to receive the prestigious 2006 Nemmers Prizes in economics and mathematics. His recognitions also include Fellow, Econometric Society, 1984; Frisch Prize Medal Co-winner, 1984; Member, American Academy of Arts and Sciences, 1993; Member, National Academy of Sciences, 1999; and President, Econometric Society, 2007.

Robert Kass
kass@stat.cmu.edu

Robert Kass is a professor in the Department of Statistics at Carnegie Mellon University. Prof. Kass received his PhD in statistics from the University of Chicago in 1980. His early work formed the basis for his book Geometrical Foundations of Asymptotic Inference, co-authored with Paul Vos. His subsequent research has been in Bayesian inference and, beginning in 2000, in the application of statistics to neuroscience. His book Analysis of Neural Data, with Emery Brown and Uri Eden, was published in 2014. Prof. Kass has served as Chair of the Section for Bayesian Statistical Science of the American Statistical Association, Chair of the Statistics Section of the American Association for the Advancement of Science, founding editor-in-chief of the journal Bayesian Analysis, and executive editor of the international review journal Statistical Science. He is an elected fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the American Association for the Advancement of Science. He has been recognized by the Institute for Scientific Information as one of the 10 most highly cited researchers, 1995-2005, in the category of mathematics.

Roger Koenker
rkoenker@uiuc.edu

Roger Koenker is the William B. McKinley Professor of Economics and professor of statistics at the University of Illinois. Much of his research deals with quantile regression. This work aims to provide a comprehensive approach to the estimation of conditional quantile functions, thus providing a more complete analysis of the stochastic relationship between economic variables than that provided by classical linear regression which restricts attention to estimation and inference about conditional mean functions. Recent work focuses more on nonparametric density estimation with penalty methods, and most recently empirical Bayes methods.

Jun Liu
jliu@stat.harvard.edu

Jun Liu is a professor of statistics at Harvard University. Prof. Liu has provided consulting to leading multinational pharmaceutical manufacturers and has served as a principal investigator in numerous National Science Foundation (NSF) and National Institutes of Health (NIH) programs. Prof. Liu is the author of the book Monte Carlo Strategies in Scientific Computing. He has published more than 150 research articles in leading scientific journals and is an Institute for Scientific Information highly-cited mathematician. In 2000 he received the Mitchell Award for the best Bayesian statistics application paper. In 2002, he received the prestigious COPSS Presidents’ Award given annually to an individual under age 40. In 2010 he received the Morningside Gold Medal in Applied Mathematics presented every three years to an individual of Chinese descent under age 45. He was selected as a Medallion Lecturer by the Institute of Mathematical Statistics (IMS) in 2002, as a Bernoulli lecturer in 2004, and as a Kuwait Lecturer in 2008 by Cambridge University. He was elected to fellow of the IMS in 2004 and fellow of the American Statistical Association in 2005. He is co-editor of the Journal of the American Statistical Association.

Andrea Montanari
montanari@stanford.edu

Andrea Montanari is an associate professor in the Department of Electrical Engineering and Department of Statistics at Stanford University. Prof. Montanari received a Laurea degree in physics in 1997, and a PhD in theoretical physics in 2001 (both from Scuola Normale Superiore in Pisa). He has been a post-doctoral fellow at Laboratoire de Physique Théorique de l'Ecole Normale Supérieure (LPTENS), Paris, and the Mathematical Sciences Research Institute, Berkeley. Since 2002 he has been Chargé de Recherche (with Centre National de la Recherche Scientifique, CNRS) at LPTENS. He first joined Stanford as faculty in September 2006. He was co-awarded the ACM SIGMETRICS best paper award in 2008. He received the CNRS bronze medal for theoretical physics in 2006, the National Science Foundation CAREER award in 2008, and the Okawa Foundation Research Grant in 2013.

Susan Murphy
samurphy@umich.edu

Susan Murphy is the H.E. Robbins Distinguished University Professor of Statistics & Professor of Psychiatry, and research professor in the Institute for Social Research at University of Michigan. She is a leading developer of the Sequential Multiple Assignment Randomized Trial (SMART) design, which has been and is being used by clinical researchers to develop adaptive interventions in depression, alcoholism, treatment of ADHD, substance abuse, HIV treatment, obesity, diabetes, and autism. Prof. Murphy is currently working as part of several interdisciplinary teams to develop clinical trial designs and learning algorithms to settings in which patient information is collected in real time (e.g., via smart phones or other wearable devices) and thus sequences of interventions can be individualized online. She is a fellow of the College on Problems in Drug Dependence, a former editor of the Annals of Statistics, a member of the Institute of Medicine, and a 2013 MacArthur Fellow.

Judith Rousseau
rousseau@ensae.fr

Judith Rousseau is a professor at the Paris Dauphine University. Her research interests include Bayesian statistics, the interaction between Bayesian and frequentist approaches, mixture distributions, and MCMC algorithms.
 

Stephen Stigler
stigler@uchicago.edu

Stephen Stigler is the Ernest DeWitt Burton Distinguished Service Professor in the Department of Statistics and the College at The University of Chicago. Prof. Stigler is an expert on the history of statistics, particularly the development of statistical methods in the natural and social sciences. Prof. Stigler is the author of The History of Statistics: The Measurement of Uncertainty Before 1900, and Statistics on the Table: The History of Statistical Concepts and Methods. He is a fellow of the American Academy of Arts and Sciences and a member of the Royal Statistical Society. Prof. Stigler served as president of the International Statistical Institute from 2003 to 2005.

Robert Tibshirani
tibs@stanford.edu

Robert Tibshirani is a professor of statistics and health research and policy at Stanford University. Prof. Tibshirani's main interests are in applied statistics, biostatistics, and data mining. He is one of the most widely cited authors in the entire mathematical sciences field having co-authored over 200 papers and three books: Generalized Additive Models (with T. Hastie), An Introduction to the Bootstrap (with B. Efron), and Elements of Statistical Learning (with T. Hastie and J. Friedman). He has made important contributions to the analysis of complex datasets and his current research focuses on problems in biology and genomics, medicine, and industry. With collaborator Balasubramanian Narasimhan, he also develops software packages for genomics and proteomics. Prof. Tibshirani is a fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the Royal Society of Canada. He won the prestigious COPSS Presidents's award in 1996, the NSERC Steacie award in 1997, and was elected to the National Academy of Sciences in 2012.