As part of ENAR's education initiative, our webinars promote continuing education for professional and student statisticians by disseminating cutting-edge knowledge to our membership. An ENAR webinar (or "WebENAR") can strengthen your background in methodology and software, provide an opportunity to learn about a topic outside of your primary area of specialization, or deepen your understanding of an area in which you already work. We invite you to participate and benefit from the expertise of some of North America's leading statisticians and biostatisticians.
The Webinar Committee of the ENAR Regional Advisory Board (RAB) is coordinating this ongoing series of 1- to 2-hour webinars given by renowned experts. Registration is free for current ENAR members. The webinars are planned to be broadly available and we encourage groups at your institution or workplace to participate together. WebENARs provide excellent learning opportunities for students and professionals alike.
Registration fees are waived for ENAR members, however, advance registration is still required for all attendees. Please email enar@enar.org if you have any questions.
DataFest 2025 Information Session for Students and Mentors
December 13, 2024
12-1 pm
Speakers:
Byron C. Jaeger, PhD, Wake Forest University School of Medicine
Anarina L. Murillo, PhD, Brown University School of Public Health
Ming Wang, PhD, Case Western Reserve University
This webinar is designed as an introduction to the DataFest 2025 data and the accompanying website/shiny application for data exploration, as well as a time to ask any questions before joining the second annual DataFest competition. This WebENAR is designed for students who want to learn more about participating, as well as anyone who is interested in serving as a mentor or judge.
For more information about DataFest, check out our website: https://www.enar.org/meetings/spring2025/program/datafest_submission.cfm
Speaker Bios:
Dr. Byron C. Jaeger: a biostatistician and data scientist in the Wake Forest University School of Medicine. My research interests include random forests, prediction modeling, blood pressure, cardiovascular disease, and cognition. I work in clinical trials such as SPRINT, LEAP, and MoTrPAC. My roles include data coordination, dynamic reporting, simulation, and analysis. I’m the developer of aorsf, an R package with fast routines to fit oblique random forests for classification, regression, and survival outcomes. I work with cognitive science experts to develop robust prediction models that can help direct cognitive screening to patients who may be at risk for developing cognitive impairment or dementia. I believe in opening science up and making it simpler, so that it’s easier for everyone to participate. A great example of this is the hypertension statistics web application I developed with my colleagues in the Jackson Heart Study Hypertension Working Group. It’s free, try it out! There are online tutorials for it here and a paper here.
Dr. Anarina Murillo is an Assistant Professor of Biostatistics at Brown University School of Public Health. Prior to that she was a Visiting Assistant Professor in the Department of Biostatistics at the NYU School of Global Public Health. Before joining NYU, she was an Assistant Professor (Research) with the Department of Pediatrics and a Senior Biostatistician with the Center for Statistical Sciences at Brown. She was an NIH T32 postdoctoral fellow in the statistical genetics and obesity training programs in the Department of Biostatistics and NIH-funded Nutrition Obesity Research Center (NORC) at the University of Alabama at Birmingham. Her research interests are broadly in statistical applications in obesity, diabetes, cardiovascular disease, infectious diseases, health disparities, and social determinants of health.
Dr. Ming Wang is a tenured Associate professor in Department of Population and Quantitative Health Sciences at Case Western Reserve University (CWRU). Before joining CWRU in Aug 2022, Dr. Wang worked in the Division of Biostatistics and Bioinformatics, Department of Public Health Sciences (PHS) at the Penn State College of Medicine as Assistant Professor (2013-2019) and Associate Professor (2019-2022). Dr. Wang received a Ph.D. degree in Biostatistics from the Department of Biostatistics and Bioinformatics at Emory University, and a bachelor degree in Applied Mathematics from Peking University in China. Her research interests include longitudinal data analysis, survival analysis, causal inference, data integration, risk prediction, high-dimensional data analysis, spatial statistics and other (bio)statistical aspects related to biomedical and human health research.
Register for Webinar on 12/13/2024.
