Featured Speakers

Christine Zhang, The New York Times

Christine Zhang is an editing resident on the New York Times graphics desk. She previously had data and graphics journalism roles at the Financial Times, Baltimore Sun, and Los Angeles Times and was a research analyst at the Brookings Institution.

Roger Peng, The University of Texas at Austin

Roger D. Peng is a professor of statistics and data sciences at The University of Texas at Austin. His current research focuses on developing theory and methods for building successful data analyses and the development of statistical methods for addressing environmental health problems.

He is the author of R Programming for Data Science and 10 other books on data science and statistics. He is also the co-creator of the Simply Statistics blog—for which he writes about statistics for the public—the Not So Standard Deviations podcast with Hilary Parker, and The Effort Report podcast with Elizabeth Matsui.

Peng is a fellow of the American Statistical Association and a recipient of the Mortimer Spiegelman Award from the American Public Health Association, which honors a statistician who has made outstanding contributions to public health.

Sara Stoudt, Bucknell University

Sara Stoudt is an applied statistician with research interests in ecology and communicating statistics. She works as an assistant professor in the department of mathematics at Bucknell University. Follow her on Twitter (@sastoudt) and check out her recent book with Deborah Nolan, Communicating with Data: The Art of Writing for Data Science.

Carol Willing, Willing Consulting

Carol Willing is the vice president of engineering at Noteable, a three-time Python steering council member, a Python core developer, a Python Software Foundation Fellow, and a Project Jupyter core contributor. In 2019, she was awarded the Frank Willison Award for technical and community contributions to Python. As part of the Jupyter core team, Willing was awarded the 2017 ACM Software System Award for Project Jupyter’s lasting influence. She’s also a leader in open science and open-source governance, serving on Quansight Labs Advisory Board and the CZI Open Science Advisory Board. She is driven to make open science accessible through open tools and learning materials.

Daniell Toth, Bureau of Labor Statistics

Daniell Toth, an active member and fellow of the American Statistical Association, is the senior research mathematical statistician in the Office of Survey Methods Research and chair of the Disclosure Review Board at the Bureau of Labor Statistics. He also serves as an associate editor for The American Statistician, Survey Methodology, and the Journal of the Royal Statistical Society A. Toth has published research in survey methodology—especially in developing tree-based methods for complex sample designs and their application to nonresponse analysis—and disclosure limitation methodology. He is the author of the R package rpms, which allows users to design consistent regression tree and forest models using survey data.

Tracy Teal, Posit, PBC

Tracy Teal is the open source program director at Posit. Previously, she was a co-founder of Data Carpentry and the executive director of The Carpentries. She developed open source bioinformatics software as an assistant professor at Michigan State University and holds a PhD in computation and neural systems from California Institute of Technology.

Tracy is involved in the open source software and reproducible research communities—including serving on advisory committees for NumFOCUS, pyOpenSci, EarthLab, and carbonplan—and has been working with open source communities; developing curricula; and teaching people how to work with data and code as a developer, instructor, and project leader throughout her career.

Felicia Simpson, Winston-Salem State University

Felicia R. Simpson is an associate professor of statistics and newly elected chair of the department of mathematics at Winston-Salem State University. Her research interests include design and analysis of clinical trials and metrics of aging. Her current research focuses on measurement and statistical modeling to characterize latent processes that underlie and conjoin different metrics for aging.

Simpson is an active member of the American Statistical Association and International Biometric Society, serving on ENAR’s regional committee. She is passionate about increasing the exposure of statistics and biostatistics to students in underrepresented populations and is a member of the ASA’s Committee on Minorities in Statistics. She also served as co-chair for the ENAR Fostering Diversity in Biostatistics Workshop.

Jeri Metzger Mulrow, Westat

Jeri Metzger Mulrow is vice president and director of statistics and data science at Westat. She oversees a staff of nearly 80 statisticians and data scientists who support an array of projects in a variety of social science and health subject areas.

Mulrow joined Westat after retiring from federal service, during which time she served as the principal deputy director at the Bureau of Justice Statistics, deputy division director at the National Center for Science and Engineering Statistics, and a mathematical statistician at the Statistics of Income Division of the Internal Revenue Service and National Institute for Standards and Technology.

Mulrow is a fellow and former vice president of the American Statistical Association.

Ming Li, PetSmart

Ming Li is a data science director at PetSmart and adjunct instructor at the University of Washington. An active American Statistical Association member, he visited 20 chapters to teach the ASA traveling course in data science, machine learning, and deep learning; organized and presented the 2018 JSM Introductory Overview Lecture, titled “Leading Data Science: Talent, Strategy, and Impact”; and served as the chair of the Quality & Productivity Section.

Li has more than 10 years of experience in data science and machine learning and has trained and mentored numerous junior statisticians, software developers, database programmers, and business analysts for Amazon, Walmart, and GE. He was also an instructor at Amazon’s internal Machine Learning University and the recipient of Amazon’s Best Science Mentor Award.