A special feature of Probability and Statistics Day at UMBC 2024 is that the conference, including the workshop, is open to all statistics graduate students from UMBC and local universities free of charge; however, REGISTRATION IS REQUIRED!
The deadline to register is
Friday, April 12, 2024.
REGISTER NOW
For more information, contact any member of the organizing committee:
Thomas Mathew
Conference Chair
410.868.4491
Seungchul Baek
410.455.2406
Ansu Chatterjee
410.455.2235
Yvonne Huang
410.455.2422
Yehenew Kifle
443.231.8368
Yaakov Malinovsky
410.455.2968
Nagaraj Neerchal
410.455.2437
Thu Nguyen
410.455.2407
DoHwan Park
410.455.2408
Anindya Roy
410.455.2435
Bimal Sinha
443.538.3012
Elizabeth Stanwyck
410.455.5731
The Department of Mathematics and Statistics at UMBC will hold the 15th Annual Probability and Statistics Day at UMBC during April 19−20, 2024. The event will consist of a half-day workshop on Friday afternoon and a full day conference on Saturday. Probability and Statistics Day at UMBC is open to statisticians from all academic institutions, government agencies, and private industries. The event is free for all statistics graduate students from UMBC and other academic institutions (registration required).
Subhashis Ghoshal
Department of Statistics
North Carolina State University
An Invitation to Bayesian Nonparametrics
Jay Bartroff
Department of Statistics and Data Sciences
The University of Texas at Austin
Optimal hypergeometric confidence sets are (almost) always intervals
Scott H. Holan
Department of Statistics
University of Missouri and US Census Bureau
Computationally efficient Bayesian unit-level models for non-Gaussian data under informative sampling
Debdeep Pati
Department of Statistics
Texas A&M University
Reconciling computational barriers and statistical guarantees in variational inference
Tian Zheng
Department of Statistics
Columbia University
Statistical challenges in climate data science
Zeytu Gashaw Asfaw
Department of Epidemiology and Biostatistics
Addis Ababa University, Ethiopia
The root-Gaussian Cox process for spatio-temporal disease mapping with aggregated data
Abdulkadir Hussein
Department of Mathematics & Statistics
University of Windsor
Ridge--Type Shrinkage Estimators in Low and High Dimensional Beta Regression Models with Applications in Econometrics and Medicine
Tommy Wright
Center Chief
Center for Statistical Research and Methodology
US Census Bureau
Visualization and Uncertainty
