Tags: General event


Bargmann Day Celebration

Bargmann Day Celebration Join us in honoring the remarkable legacy of Dr. Rolf E. Bargmann as we celebrate a tremendous act of generosity from Dr. Bargmann’s daughters, Monika, Eve, Cori, and Dorie as they pledge a remarkable $50,000 to the Bargmann Statistics Fund.  This event, as well as the Bargmann lab dedication, will be held on Monday, March 25, 2024 at 4PM. Refreshments will be served in the Cohen Room following the ceremony. Below…


Joshua Lukemire

A general framework for brain network extraction from fMRI data with repeated measurements Abstract: We introduce a general framework for decomposing brain function into functional brain networks for multi-subject data with repeated measurements and covariate effects. This general method provides a much-needed tool for investigating brain networks and their differences in imaging studies with complex study designs including longitudinal and/or…


Hui Yi

How can emerging statistical methodologies improve the global response to human trafficking? Abstract: Having accurate prevalence data is critical for enabling informed decisions about how to allocate scarce resources to strengthen human trafficking (HT) response. Traditional prevalence estimation strategies, namely those utilizing probability sampling designs that are based on combinations of stratified and multistage sampling, have long been…


UGA DSAI Summer Camp 2024

Encouraged by the success of the 2023 Data Science & Artificial Intelligence Summer Camp and due to popular demand, the Department of Statistics at the University of Georgia is once again partnering with Data Scientists at Wells Fargo to offer a Data Science & Artificial Intelligence Camp this summer. This camp will be held in person on the campus of University of Georgia. About 30 high school students will be selected to participate in…


Xiao Song

Evaluating biomarkers for treatment selection from reproducibility studies Abstract We consider evaluating new or more accurately measured predictive biomarkers for treatment selection based on a previous clinical trial involving standard biomarkers. Instead of rerunning the clinical trial with the new biomarkers, we propose a more efficient approach which requires only either conducting a reproducibility study in which the new biomarkers and…


He Tang

On estimation and order selection for multivariate extremes via clustering Abstract: We investigate the estimation of multivariate extreme models with a discrete spectral measure using clustering techniques. The primary innovation involves devising a method for selecting the appropriate order that not only consistently identifies the true order in theory but also has a straightforward and easy implementation in practice. Specifically, we…


Bimal Sinha

Confidence ellipsoids of a multivariate normal mean vector based on noise perturbed and synthetic data with applications Abstract: We discuss at length the problem of constructing a confidence ellipsoid of a multivariate normal mean vector based on a random sample from it. The central issue at hand is the sensitivity of the original micro data and hence the data cannot be directly used/analyzed. We consider a few perturbations of the original…


Hiya Banerjee

The Impact Of Treatment Discontinuation Due Adverse Events On Efficacy In An Oncology Clinical Trial Abstract Randomized clinical trials persist as the gold standard for evaluating the efficacy and safety of new treatments. However, in clinical trials of reasonable size and duration, it is common for some patients to deviate from their assigned study treatment due to various reasons. One such deviation is treatment discontinuation resulting from…


Ruiyan Luo

Fully Functional Neural Networks for Functional Regression Abstract We consider evaluating new or more accurately measured predictive biomarkers for treatment selection based on a previous clinical trial involving standard biomarkers. Instead of rerunning the clinical trial with the new biomarkers, we propose a more efficient approach which requires only either conducting a reproducibility study in which the new biomarkers and standard…


Xiaoming Zhai

AI and the formative Assesment: The Train Has Left the Station Abstract: Researchers have been questioning AI --whether we can and should use AI for formative assessment. AI is already being employed, for better or worse, to facilitate formative assessment in various educational contexts. In this talk, Dr. Zhai will demonstrate research on AI-based assessment in science education. He will respond to the many concerns raised in the field…
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