Statistics at UC Berkeley

Max Fathi, UC Berkeley (Speaker)
Oct 9, 2015 1:10pm 891 Evans Hall
In this talk, I will explain how the gradient flow structure of diffusion equations suggests a way of studying convergence of sequences of such processes to some limit, and how this approach can be implemented to prove convergence to the hydrodynamic limit for a particular model of interacting spins, with explicit quantitative bounds, following a work of N. Grunewald, F. Otto, C. Villani and M....
Quantitative Convergence of Interacting Spin Systems
Haoyang Liu, University of California, Berkeley (Speaker - Featured)
Oct 13, 2015 11:00am 639 Evans Hall
Prabhat, NERSC, Lawrence Berkeley Lab
Oct 13, 2015 4:10pm 1011 Evans Hall
Lawrence Berkeley National Lab and NERSC are at the frontier of scientific research. Historically, NERSC has provided leadership computing for the computational science community, but we now find ourselves tackling Big Data problems from an array of observational and experimental sources. In this talk, I will review the landscape of Scientific Big Data problems at all scales, spanning astronomy,...
Guillaume Barraquand, Department of Mathematics, Columbia
Oct 14, 2015 3:10pm 332 Evans Hall
We consider a model of random walks in space-time random environment, with Beta-distributed transition probabilities. This model is exactly solvable, in the sense that the law of the (finite time) position of the walker can be completely characterized by Fredholm determinantal formulas. This enables to prove a limit theorem towards the Tracy-Widom distribution for the second order corrections to...
Perry de Valpine, UC Berkeley
Oct 14, 2015 4:00pm 1011 Evans Hall
There is a large gap between new ideas constantly emerging in the Statistics literature and methods used by scientists in various application domains for problem-specific hierarchical models. A major reason for this gap is the state of general statistical software. Implementing a new method that can be used for a wide range of models can require re-inventing systems for model specification,...
Neyman Seminar

Statistics at UC Berkeley: We are a community engaged in research and education in probability and statistics. In addition to developing fundamental theory and methodology, we are actively involved in statistical problems that arise in such diverse fields as molecular biology, geophysics, astronomy, AIDS research, neurophysiology, sociology, political science, education, demography, and the U.S. Census. We have forged strong interdisciplinary links with other departments and areas of study, particularly biostatistics, mathematics, computer science, and biology, and actively seek to recruit graduate students and faculty who can help to build and maintain such links. We also offer a statistical consulting service each semester.