Summer/Fall 2020 Webinars on Statistical Methods in the Physical Sciences

Hosted by the STAMPS research group at CMU

Webinars are open to all interested members of the scientific community.

Program Committee: Mikael Kuusela, Ann B. Lee, Larry Wasserman
Coordinator and Webmaster: Nic Dalmasso

Webinars are held monthly, unless otherwise stated, on the 2nd Friday of each month at 1:30-2:30 PM Eastern Time (10:30-11:30AM PT, 6:30-7:30PM UK)

*** To connect to the webinars please subscribe to the mailing list here ***
Webinar recordings are available on our Youtube channel here
A Google Calendar for webinars is available here

July 10: Adam Sykulski (Department of Mathematics and Statistics, Lancaster University) #

Title: Stochastic modeling of the ocean using drifters: The Lagrangian perspective
[Talk Details] [Talk Recording]

Aug 14: Tommaso Dorigo (INFN-Padova) #

Title: Frequentist Statistics, the Particle Physicists’ Way: How To Claim Discovery or Rule Out Theories
[Talk Details] [Talk Recording] [Talk Slides]

Sept 11: Parker Holzer (Department of Statistics & Data Science, Yale University) #

Title: Discovering Exoplanets With Hermite-Gaussian Linear Regression
[Talk Details] [Talk Recording] [Talk Slides]

Oct 9: Amy Braverman (Jet Propulsion Laboratory, California Institute of Technology) #

Title: Post-hoc Uncertainty Quantification for Remote Sensing Observing Systems
[Talk Details] [Talk Recording] [Talk Slides]

Oct 23: Collin Politsch (Machine Learning Department, Carnegie Mellon University) #

Title: Three-dimensional cosmography of the high redshift Universe using intergalactic absorption
[Talk Details][Talk Recording] [Talk Slides]

Nov 13: Murali Haran (Department of Statistics, Pennsylvania State University) #

Title: Statistical Methods for Ice Sheet Model Calibration
[Talk Details][Talk Recording] [Talk Slides]

Note: December’s webinar will be held on the 1st Friday (Dec. 4), instead of the 2nd

Dec 4: Jenni Evans (Department of Meteorology & Atmospheric Science, Pennsylvania State University) #

Title: Unscrambling ensemble simulations to improve hurricane forecasts
[Talk Details] [Talk Recording]