Making an Impact through Statistical Leadership: Methods, Collaboration, and Beyond

Lucy D'Agostino McGowan Chair
Wake Forest University
 
Ana Maria Ortega-Villa Panelist
National Institutes of Health
 
Irina Gaynanova Panelist
University of Michigan
 
Eric J. Daza Panelist
Boehringer Ingelheim
 
Sandra Safo Panelist
University of Minnesota
 
Jennifer Bobb Panelist
Kaiser Permanente Washington
 
Lucy D'Agostino McGowan Organizer
Wake Forest University
 
Tuesday, Aug 4: 10:30 AM - 12:20 PM
1458 
Topic-Contributed Panel Session 
Thomas M. Menino Convention & Exhibition Center 
Room: CC-156C 
This panel session features recent winners of the Committee of Presidents of Statistical Societies (COPSS) Emerging Leader Award (2024–2025), recognized for their potential to shape the future of statistical science. Panelists will share perspectives on advancing innovative methods, building collaborative research programs, and communicating statistical insights across diverse audiences.

The discussion will highlight different pathways for statisticians to make a broad impact, including developing new statistical method, leading interdisciplinary teams, mentorship, influencing policy and practice, and engaging effectively with the public. Panelists will also reflect on their experiences navigating leadership roles at an early stage in their careers and offer practical advice for cultivating leadership skills.

The session is designed to inspire and equip attendees-particularly students and early-career researchers-with strategies for expanding their influence within the profession and beyond. Interactive discussion and audience questions will provide an opportunity to engage directly with the panelists, making this session relevant not only for those seeking to enhance their own leadership but also for anyone interested in the role of statisticians in addressing pressing scientific and societal challenges.

Applied

Yes

Main Sponsor

Committee on Women in Statistics

Co Sponsors

Biometrics Section
Caucus for Women in Statistics and Data Science
ENAR