TRIADS has undergone a leadership transition this semester, bringing a new face to its team.

Bo Li, the Stanley A. Sawyer Professor in Statistics and Data Science, has joined TRIADS as its co-director. Tammy English, previously associate director of TRIADS, now co-directs alongside Li.

TRIADS Speaker Series: Rebecca Nugent
Thursday, November 21, Noon
Umrath Lounge

RSVP

We are surrounded by data, but most people are not yet comfortable having data science and/or AI as part of their work or daily lives. Moreover, people tend to make decisions under uncertain, dynamic, and resource-constrained circumstances, often incorporating concerns about risk, equity and trust. This disconnect is contributing to growing disparities in use across demographic groups and sectors. Data science and AI education have never been more important. 

In this talk, we’ll look at the data science and AI education efforts of two large NSF-funded initiatives centrally housed at Carnegie Mellon University — the NSF AI Institute for Societal Decision Making and the sports-analytics focused SCORE network — to build pipelines and train the public to use data science and AI to positively impact society.

For Grad Students: Breakfast with Rebecca Nugent
Thursday, November 21, 8:30 a.m.
TRIADS Office, Jolley Hall 420

RSVP

Join Dr. Rebecca Nugent for a breakfast and networking event. Only a couple of spots are available, so please RSVP as soon as possible.

How Statistics Can Advance Large Language Models: Fairness Alignment and Watermarking
Speaker: Weijie Su, University of Pennsylvania
Presented by the Department of Statistics and Data Science

Wednesday, November 20, 11 a.m.
Duncker Hall 101

Large language models (LLMs) have rapidly emerged as a transformative innovation in machine learning. However, their increasing influence on human decision-making processes raises critical societal questions. In this talk, we will demonstrate how statistics can help address two key challenges: ensuring fairness for minority groups through alignment and combating misinformation through watermarking.

Accurate and efficient data point removal for high-dimensional settings
Speaker: Arian Maleki, Columbia University.
Presented by the Department of Statistics and Data Science

Friday, November 22, 10 a.m.
Preston M. Green Hall, Rodin Auditorium

Large language models (LLMs) have rapidly emerged as a transformative innovation in machine learning. However, their increasing influence on human decision-making processes raises critical societal questions. In this talk, we will demonstrate how statistics can help address two key challenges: ensuring fairness for minority groups through alignment and combating misinformation through watermarking.

If you are interested in any of the grant opportunities below, please reach out to Dr. Bhavna Hirani, Senior Research Development Associate, for assistance.

NSF: Human-Environment and Geographical Sciences Program (HEGS)
Proposal Due Date: February 3, 2025

Supports fundamental research that examines how human behavior interacts with environmental and social processes, advancing geographical theory and geospatial methods through rigorous, impactful studies.

DoD: Minerva Research Initiative
White paper due date: November 29, 2024

The Minerva Research Initiative supports social science research aimed at improving our basic understanding of security, broadly defined. All supported projects are university-based and unclassified, with the intention that all work be shared widely to support thriving stable and safe communities. The goal is to improve DoD’s basic understanding of the social, cultural, behavioral, and political forces that shape regions of the world of strategic importance to the U.S.

NIH: BRAIN Initiative: Brain Behavior Quantification and Synchronization – Next Generation Sensor Technology Development
Proposal due date: June 13, 2025

This initiative is intended to support the development of next-generation sensor technologies and bioelectronic devices. The BRAIN Initiative funding opportunities broadly support: 1) development of tools for simultaneous, multimodal measurement of behavior within complex, dynamic physical and/or social environments and synchronize these data with simultaneously-recorded neural activity and 2) development of novel conceptual and computational models that capture dynamic behavior-environment relationships across multiple timescales and that can integrate correlated neural activity into the model.

NSF: Emerging Mathematics in Biology (eMB)
Due date: March 3, 2025

This program seeks to stimulate the development of innovative mathematical theories, techniques, and approaches to investigate challenging questions of great interest to biologists and public health policymakers. It supports truly integrative research projects in mathematical biology that address challenging and significant biological questions through novel applications of traditional, but nontrivial, mathematical tools and methods or the development of new mathematical theories.

NIH: Virtual NIDA Workshop on Geospatial Data Science
Webinar Date: December 3, 2024

The goal of this workshop is to bring together research communities in the forefront of leveraging geospatial data in drug use and addiction research. Please join us to explore how we can harness the power of geospatial data science to advance our understanding of the epidemiology, prevention, and treatment of drug use and addiction. 

Do you have feedback or want to submit an item for a future newsletter? Let us know at triads@wustl.edu.