COPSS-NISS Leadership Webinar: Leadership in Statistical Research: Pivoting for Impact and Success

The COPSS-NISS Leadership Webinar presents “Leadership in Statistical Research: Pivoting for Impact and Success,” featuring distinguished panelists Qi Long, Ph.D. (Professor of Biostatistics, Computer and Information Science, and Statistics and Data Science, University of Pennsylvania) and Nicole Lazar, Ph.D. (Department Head and Professor of Statistics, Penn State University). This session explores strategic career pivots, interdisciplinary collaborations, and leadership in statistical research across academia, industry, and government. Attendees will gain insights into navigating career transitions, fostering impactful research, and advancing professional growth. Designed for statisticians, data scientists, and researchers at all levels, this discussion provides valuable perspectives on adapting to the evolving landscape of statistics and data science. Join us for an engaging conversation on leadership, impact, and success in statistical research!

Download the flyer here:  March25-flyer.pdf (444.57 KB)

Panelists

Qi Long, Ph.D., Professor of Biostatistics, Statistics and Data Science, and Computer and Information Science; Associate Director for Quantitative Data Science, Abramson Cancer Center; Associate Director, Institute for Biomedical Informatics, University of Pennsylvania.

Nicole Lazar, PhD, Department Head and Professor of Statistics at Penn State University

Moderator

Sandra Safo, PhD, Associate Professor, Division of Biostatistics & Health Data Science, University of Minnesota

About the Speakers

Qi Long, Ph.D. is a Professor of Biostatistics at the Perelman School of Medicine at the University of Pennsylvania, with joint appointments in the Department of Computer and Information Science at the School of Engineering and Applied Science and the Department of Statistics and Data Science at The Wharton School. He is also Vice Chair of Faculty Professional Development in the Department of Biostatistics, Epidemiology and Informatics, founding director of the Penn Center for Cancer Data Science, Associate Director for Cancer Informatics of the Penn Institute for Biomedical Informatics, and inaugural Associate Director for Quantitative Data Science of the Abramson Cancer Center. His research program marries innovative statistical, machine learning (ML) and artificial intelligence (AI) research with impactful biomedical research. His research has appeared in high-impact biomedical journals such as Nature Medicine and JAMA Oncology, leading statistical journals such as Annals of Statistics and Journal of the American Statistical Association, and leading AI/ML conferences such as ICML and NeurIPS. Dr. Long’s methodological research has been supported by NIH, PCORI, NSF and ARPA-H. In addition, Dr. Long has led coordinating center for large-scale research networks and multi-site clinical studies. He currently co-directs the Coordinating Center for the Premedical Cancer Immunotherapy Network for Canine Trials (PRECINCT), part of NCI’s Cancer Moonshot Initiative. Dr. Long is a Senior Editor for Cancer Research, and Executive Editor for Statistical Analysis and Data Mining: The ASA Data Science Journal. Dr. Long is an elected fellow of the American Association for the Advancement of Science (AAAS), the American Statistical Association (ASA), and the American Medical Informatics Association (AMIA). See Academic Profile.

Nicole Lazar, PhD is the Department Head and Professor of Statistics at Penn State University. Lazar received her PhD in Statistics from the University of Chicago, her MS in Statistics from Stanford University, and her BA in Psychology and Statistics from Tel Aviv University. Her research interests include the foundations of statistical inference, statistical reform, and the analysis of functional neuroimaging data. She has worked on fundamental inferential topics such as model selection, multiple testing problems, and likelihood theory, specifically in the context of modern large-scale data analysis problems. She has done pioneering work on the statistical analysis of cognitive neuroscience data, with a focus on functional magnetic resonance imaging (fMRI). Most recently, Lazar has been involved in the application of topological data analysis methods to scientific questions of interest in psychology and climatology. These techniques are at the interface of statistics, mathematics, and computer science, and exemplify her cross-disciplinary approach to research. Lazar is the author of the book The Statistical Analysis of Functional MRI Data published by Springer. She is past Editor of The American Statistician and was a co-Editor of a Special Issue of The American Statistician on Statistical Inference in the 21st Century: A World Beyond p<0.05. She is an Elected member of the International Statistical Institute, a Fellow of the American Statistical Association, and a Fellow of the Institute of Mathematical Statistics. Lazar also served as President of the Caucus for Women in Statistics in 2019. She has an extensive record of service to the statistics profession. Prior to joining Penn State in 2020, she was on the faculty of Carnegie Mellon University and the University of Georgia, where she was Interim Department Head from 2014 to 2016. See Academic Profile

About the Moderator

Sandra Safo, PhD, is an Associate Professor in the Division of Biostatistics and Health Data Science and a Graduate Faculty of Data Science in the College of Science and Engineering at the University of Minnesota. Her research focuses on developing robust, explainable, and practical statistical and machine learning methods for high-dimensional data to advance clinical translational research and precision medicine. Her methodological expertise includes classification, discriminant analysis, clustering, dimension reduction, deep learning, and sample size estimation, with a particular interest in functional data analysis and social determinants of health. Dr. Safo’s research is supported by multiple PI grants, including the Maximizing Investigators Research Award (MIRA, R35 from NIGMS) for early-stage investigators and administrative supplements from the National Institute on Aging (NIA) and the Office of Data Science and Strategy.  Recognized for her contributions to the field, she has received numerous prestigious honors, including the 2024 COPSS Emerging Leader Award and the University of Minnesota McKnight Land-Grant Professorship (2023-2025). She is a standing member of the NIH Analytics and Statistics for Population Research Panel A (ASPA) and an elected member of the International Statistical Institute (ISI). 

About the COPSS-NISS Leadership Webinar Series

COPSS (Committee of the Presidents of Statistical Societies) and NISS have come together to organize and host a new webinar series focusing on leadership in statistics and data science. Plan to attend these webinars every month during the academic year! Visit the COPSS-NISS Leadership Series Page for previous webinars.

The COPSS-NISS Leadership Webinar Series is co-organized by the Committee of the Presidents of Statistical Societies (COPSS) Emerging Leaders in Statistics and the National Institute of Statistical Sciences (NISS). The purpose of the webinar series is to promote leadership skills for members of the statistical societies at any stage in their careers. The series features conversations with leaders throughout the discipline, including leaders from major academic and government institutions, and companies. Invited speakers share their leadership stories and answer questions about their experiences. Each webinar is moderated by a member of the COPSS Emerging Leaders in Statistics program.

Access the Full COPSS-NISS Leadership Webinar Series YouTube Playlist | COPSS-NISS Leadership Webinar Series: https://www.youtube.com/playlist?list=PLoRtupvDJTjvFukMcO6NfDr0GvxDsIj81