Modeling Data in the Tidyverse

Carrie Wright, PhD, serves as a Senior Staff Scientist at Fred Hutchinson Cancer Center and holds an affiliated faculty position at Johns Hopkins Bloomberg School of Public Health, where she focuses on making data science and computational biology more accessible to diverse audiences. Her expertise spans multiple domains, teaching courses including "AI for Decision Makers," "AI for Efficient Programming," "Avoiding AI Harm," "Best Practices for Ethical Data Handling," "Data Management and Sharing for NIH Proposals," and "Write Smarter with Overleaf and LaTeX." Her distinguished career includes significant contributions as a former Assistant Scientist in Biostatistics at Johns Hopkins and postdoctoral research at the Lieber Institute for Brain Development, where she studied genetic mechanisms in psychiatric disease. As a member of the Open Case Studies team, the Genomic Data Science Community Network, and chair of the ITCR OPEN Group, she demonstrates her commitment to advancing science, medicine, and social justice through accessible data science education. Her innovative work includes co-founding the LIBD rstats club and teaching at various institutions, including the Baltimore Underground Science Space and Johns Hopkins Center for Talented Youth.

Dr. Roger D. Peng is a Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health and serves as a Co-Editor of the Simply Statistics blog. He earned his PhD in Statistics from the University of California, Los Angeles, and is recognized for his research in air pollution, health risk assessment, and statistical methods for environmental data. In 2016, he received the Mortimer Spiegelman Award from the American Public Health Association, honoring his significant contributions to health statistics. Dr. Peng developed the Statistical Programming course at Johns Hopkins to equip students with essential computational tools for data analysis. Additionally, he is a national leader in promoting reproducible research practices and serves as the Reproducible Research editor for the journal Biostatistics. His interdisciplinary research has been published in prestigious journals, including the Journal of the American Medical Association and the Journal of the Royal Statistical Society. He has authored over a dozen software packages that implement statistical methods for environmental studies and reproducible research, and he regularly conducts workshops and tutorials on statistical computing and data analysis.

César Sáez Navarrete is a distinguished academic and researcher at the Pontifical Catholic University of Chile (UC), where he holds a Doctorate in Engineering Sciences and specializes in chemical engineering. With a robust educational background, including postdoctoral studies at the University of Edinburgh, Dr. Sáez Navarrete directs various projects and supervises postgraduate students in critical areas such as bioenergy, biofuels, electrophotocatalysis using nanomaterials, and the bioremediation of petroleum-contaminated sites. He serves as the Director of the Renewable Energy and Waste Laboratory and is the Scientific Director of the Center for Nanotechnology and Advanced Materials (CIEN-UC). His work not only focuses on innovative technologies for environmental remediation but also emphasizes sustainable practices within energy production. Dr. Sáez Navarrete is actively involved in mentoring future engineers, contributing to their development through hands-on research and practical applications. His extensive experience and commitment to sustainability make him a key figure in advancing research and education in engineering at UC Chile.

Dr. Stephanie Hicks is an Assistant Professor in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health, where she specializes in developing statistical methods and software for the analysis of genomics data. Her research focuses on addressing computational challenges in areas such as single-cell genomics, epigenomics, and spatial transcriptomics, contributing to a better understanding of human health and disease. Dr. Hicks is also actively involved in education, teaching courses on data science and genomics analysis. She co-hosts The Corresponding Author podcast and is a co-founder of R-Ladies Baltimore, an initiative aimed at promoting gender diversity in the R programming community. Dr. Hicks holds a B.S. in Mathematics from Louisiana State University and both an M.A. and Ph.D. in Statistics from Rice University. Her work has earned her several prestigious awards, including the Teaching in the Health Sciences Young Investigator Award and the COPSS Emerging Leader Award from the American Statistical Association. As a dedicated advocate for diversity, equity, and inclusion in statistics and data science, Dr. Hicks continues to make significant contributions to both her field and the broader academic community.