AI, Statistics and Data Science in Practice Webinar: ML and Bayesian Geospatial Approaches for Prediction of Opioid Overdose Deaths

Tuesday, April 22, 2025 - 12:00pm to 1:30pm

Overview

Join us for the next session of the NISS AI, Statistics, and Data Science in Practice webinar series, featuring Dr. Soledad Fernández, Distinguished Professor and Division Chief of Biostatistics and Population Health at The Ohio State University. Dr. Fernández also serves as the Director of the Center for Biostatistics in the Department of Biomedical Informatics, College of Medicine. In this talk, Dr. Fernández will discuss the application of machine learning (ML) and Bayesian geospatial modeling for predicting opioid overdose deaths. As the opioid crisis continues to impact communities nationwide, leveraging statistical and AI-driven approaches can provide critical insights into geographic and population-level risk factors. This presentation will explore how advanced modeling techniques can enhance surveillance efforts, inform public health interventions, and improve policy decision-making.

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Speaker

Dr. Soledad Fernández, Distinguished Professor and Division Chief of Biostatistics and Population Health at The Ohio State University. Dr. Fernández also serves as the Director of the Center for Biostatistics in the Department of Biomedical Informatics, College of Medicine.

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. Soledad Fernández is a professor and serves on the roles of Vice-Chair for Collaborative Research, Leader of the Biostatistics and Population Health Science Division in the Department of Biomedical Informatics. She is also the Director of the Center for Biostatistics (CFB) at The Ohio State University. In these roles she works with faculty and staff in BMI and CFB to build interdisciplinary teams to advance biomedical and translational research expertise and capabilities in BMI. As Director of CFB she collaborates extensively with researchers in the Comprehensive Cancer Center (CCC) and Center for Clinical and Translational Science Institute (CTSI), serving as the biostatistics core director on multiple awards and grants at OSU affiliated with these two centers. Examples of these transdisciplinary, multi-site studies and cores are: OSUCCC-Biostatistics Shared Resource, PaTH, STOP-COVID, RADx-TDR: D4I, Healing Communities Study. She has over 170 publications, a large portion of which are with cancer investigators within the CCC. Her current main area of interest is in the development, validation and implementation of clinical/research data coordinating centers to support and enhance scientific rigor and reproducible biomedical research. She has been a part of the Center for Biostatistics since 2003, serving as Associate Director from 2009 to 2012. Dr. Fernandez has been a part of the OSU community since 2001, where she started in the Department of Statistics, where she taught undergraduate and graduate courses in the area of mathematical statistics and regression analysis for the engineering sciences. Previous to joining the university community, Dr. Fernandez received a Master in Statistics in 1998 and a joint Ph.D. in Statistics & Animal Breeding and Genetics in 2001 from Iowa State University.

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.

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