Overview
Overview Coming Soon!
Speaker
Dr. Amy McGovern, Lloyd G. and Joyce Austin Presidential Professor, School of Meteorology and School of Computer Science and Director, NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES), University of Oklahoma
Moderator
Nancy McMillan, Data Science Research Leader, Health Research & Analytics Business Line at Battelle
Abstract
Abstract Coming Soon!
Event Disclaimer
The views and opinions expressed by the speakers during this event are their own and do not necessarily reflect the views, positions, or policies of their employers, affiliated organizations, or any other entity. The speakers are participating in a personal capacity, and their statements should not be attributed to their respective companies or institutions.
About the Speaker
Dr. Amy McGovern, Lloyd G. and Joyce Austin Presidential Professor, School of Meteorology and School of Computer Science and Director, NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES), University of Oklahoma
About the Moderator
Nancy McMillan currently serves as Data Science Research Leader within Battelle’s Health Research & Analytics Business Line. For a diverse set of federal government clients, she currently leads development of a large language model (LLM) based biocuration acceleration pipeline and user tool, development of pipelines, analytics, and visualizations of electronic initial case reporting data, and development of analytical methods for achieving abbreviated new drug application (ANDA) approval for an agile drug manufacturing technology. Nancy has a long history of collaborative work across Battelle bringing statistics and machine learning to Battelle’s deep capability in biology, chemistry, and material science. As a researcher and Project Management Professional, Nancy has worked and published on environmental exposure and risk assessment; transportation safety benefits; quantitative risk assessment related to chemical, biological, radiological and nuclear (CBRN) terrorism; bio surveillance; and bioinformatics. She managed the Health Analytics Division from 2017-2023, a team of approximately 100 data scientists that supports Battelle’s contract research business. Nancy is a member of the Board of Trustees for the National Institute of Statistical Sciences (NISS), the Chair of NISS’s Affiliates Committee, and a member of the Organ Procurement and Transplantation Network’s Data Advisory Committee.
About AI, StAtIstics and Data Science in Practice
The NISS AI, Statistics and Data Science in Practice is a monthly event series will bring together leading experts from industry and academia to discuss the latest advances and practical applications in AI, data science, and statistics. Each session will feature a keynote presentation on cutting-edge topics, where attendees can engage with speakers on the challenges and opportunities in applying these technologies in real-world scenarios. This series is intended for professionals, researchers, and students interested in the intersection of AI, data science, and statistics, offering insights into how these fields are shaping various industries. The series is designed to provide participants with exposure to and understanding of how modern data analytic methods are being applied in real-world scenarios across various industries, offering both theoretical insights, practical examples, and discussion of issues.
Featured Topics:
- Veridical Data Science - Speaker: Bin Yu, October 15,2024
- Random Forests: Why they Work and Why that’s a Problem - Speaker: Lucas Mentch, November 19, 2024
- Causal AI in Finance in Business Practices - Speakers: Victor Lo, and Victor Chen, January 24, 2025
- Large Language Models: Transforming AI Architectures and Operational Paradigms - Speaker: Frank Wei, February 18, 2025
- Machine Learning for Airborne Biological Hazard Detection - Speaker: Jared Schuetter, March 11, 2025
- Experimental Design and Causal Inference
- Statistics and Experimentation Needs in Industry
- Generative AI for Use in Industry
- Uncertainty Quantification for Random Forests
- Deep Learning Methods for Closed-Loop Neuromodulation
- Causal Inference in Marketing Analytics
- Practical Return on AI Investment
Event Type
- NISS Hosted