2013 Tsinghua University Pao-Lu Hsu Distinguished Lecture
Speaker: Peter J. Bickel
Professor of University of California, Berkeley
Member of the U. S. National Academy of Sciences
Fellow of the American Academy of Arts and Sciences
Foreign Member of the Royal Netherlands Academy of Arts and Sciences
Time: 16:30-17:30, Sep 25 (Wed.), Sep 27 (Fri.)
Place: Lecture Hall, Floor 3, Jin Chun Yuan West Building, Tsinghua University
Titles and Abstracts
Lecture 1
Title: Some examples of statistical inference in genomics
Abstract: I’ll talk about two examples of how substantive biological questions posed to us by our collaborators in the ENCODE and modENCODE consortia led to major new statistical problems, a model for randomness in the genome and a way of assessing reliability without knowing ground truth.
(Joint work in parts with: J. B. Brown, H. Huang, Q. Li, N Zhang and NP Boley)
Lecture 2
Title: Topics in Nonparametric Inference for unlabeled network models
Abstract: In Bickel and Chen PNAS (2009) we introduced a “nonparametric” model for unlabeled graphs with L=average degrees ranging from >>log (n) to O (n) and studied it in relation to “block models”.
We will give an overview of our work in this regime including new results on maximum and variational likelihood for block models as well bootstrap methods and applications to testing for the nonparametric model.
(Joint work (on various parts) with A. Chen, D. Choi, E Levina and S. Bhattacharyya)
Introduction of Peter J. Bickel
Peter Bickel is an American statistician, Professor of Statistics in University of California, Berkeley. He studied physics at the California Institute of Technology. He graduated from University of California, Berkeley, with a Ph.D., in 1963.
Prof. Peter Bickel has been a leading figure in the field of statistics in the 43 years since he received his Ph.D. in Statistics at the age of 22. He is widely recognized as one of the greatest statisticians of our time in any metrics: breadth, depth and productivity. He has made wide-ranging and far-reaching contributions to the discipline of statistics. He has pioneered the research in many statistical disciplines and has made fundamental contributions to many areas in statistics. These include robust statistics, decision theory, semiparametric modeling, bootstrap, nonparametric modeling, machine learning, computational biology, and many other areas (e.g. transportation and genomics) where statistics and quantitative approaches play an important role. His exceptional record of research accomplishment is evidenced by his exceptionally many publications in the very top ranking journals in the field of statistics.
Prof. Bickel’s wide-ranging and far-reaching contributions to statistics have been significantly recognized internationally by numerous awards and honors. These include the first recipient of The COPSS Presidents Award, and The Wald Lecturer in 1980. His work has also been greatly recognized outside the statistical profession. These include his John D. and Catherine T. MacArthur Foundation Fellowship in 1984. He also elected to the fellow of the American Academy of Arts and Sciences, the National Academy of Sciences, and the Royal Netherlands Academy of Arts and Sciences. He is past President of the Bernoulli Society and of the Institute of Mathematical Statistics.
Source: http://en.wikipedia.org/wiki/Peter_J._Bickel
http://orfe.princeton.edu/conferences/frontiers/Biography.pdf
