Dr. Sarah Lotspeich is an Assistant Professor of Statistics at Wake Forest University. Sarah earned her Ph.D. in Biostatistics from Vanderbilt University in 2021 and completed a postdoctoral fellowship in Biostatistics at the University of North Carolina at Chapel Hill in 2022. Her research tackles challenges in analyzing error-prone and incomplete real-world data, focusing on international HIV cohorts, electronic health records, and health disparities, and in developing statistical models with censored covariates, applicable to Huntington’s disease. Sarah has published in peer-reviewed biostatistics, bioinformatics, clinical research, and epidemiology journals. She enthusiastically mentors student research and co-leads collaborative labs at Wake Forest and the University of North Carolina at Chapel Hill. She co-organizes Florence Nightingale Day at Wake Forest annually, engaging local middle and high school students in statistics and data science, and holds elected positions in ENAR and other professional organizations. Outside of academia, Sarah has also worked in various data-centric roles with a government health department, a Fortune 500 energy corporation, and a social media tech company. She was raised by rocket scientists on the east coast of Florida and earned her BS in Statistics from the University of Florida.

Dr. Wei Chen is Professor of Pediatrics at the University of Pittsburgh and the Founding Director of the Statistical Genetics Core at UPMC Children’s Hospital of Pittsburgh. He holds a secondary appointment in the Department of Biostatistics and Health Data Science. He is a nationally recognized biostatistician and computational biologist specializing in bulk and single-cell multi-omics, spatial transcriptomics, and pulmonary medicine. He co-leads NIH- and DoD-funded collaborative programs in childhood asthma and pediatric scleroderma and has pioneered statistical and machine-learning frameworks as the analytic backbone for these studies. He has published 190 papers, including senior-author publications in premier journals spanning both methodology (Nature Machine Intelligence, Biometrics, AoAS, Nature Communications) and biomedical science (JAMA, AJRCCM, ERJ, Lancet Respiratory Medicine). Dr. Chen is an elected Fellow of the American Thoracic Society and served on the Scientific Advisory Board. He will serve as President of the Chinese-American Lung Association in 2026 to bridge data science and pulmonary medicine nationally and internationally. As a dedicated mentor, he has trained more than 30 PhD students, postdocs, medical fellows, and junior faculty, who have received multiple awards at statistical and clinical conferences. His leadership ensures that biostatistics drives discovery, translation, and clinical impact in pediatric diseases.

Dr. Juan Celedón is a distinguished physician-scientist and Professor of Pediatrics and Medicine, internationally known for his contributions to asthma genetics, environmental epidemiology, and health disparities. Dr. Celedón is a former President of the American Thoracic Society (ATS), an elected member of the American Society for Clinical Investigation and the Association of American Physicians, and a recipient of the ATS’ J. Burns Amberson Lecture. He has led more than ten NIH R01 awards focused on gene–environment interactions and genomics in Hispanic/Latino children and generated the largest nasal multi-omics datasets in pediatric asthma, leading to publications in NEJM, JAMA, AJRCCM, JACI, and Lancet Respiratory Medicine. Dr. Celedón has collaborated closely with Dr. Chen for over a decade, integrating advanced biostatistics and multi-omics analytics into the design and interpretation of his population studies. Their partnership has reshaped the molecular understanding of childhood asthma and generated >70 high-impact publications, half first-authored by biostatistics trainees. Dr. Celedón’s commitment to rigorous, team-oriented science and his leadership in national and international asthma consortia have made him a pivotal contributor to advancing precision medicine in respiratory health.

Dr. Erick Forno is Professor of Pediatrics and Vice Chair for Clinical Research at Indiana University School of Medicine and a leading pediatric pulmonologist specializing in asthma, obesity-related lung disease, epigenetics, and gene–environment interactions. His research bridges clinical care and molecular epidemiology, integrating advanced biostatistical and computational tools to address health disparities in asthma. A long-term collaborator of Dr. Chen, Dr. Forno co-leads multi-omic investigations in childhood asthma and has co-invented two U.S. patents with Dr. Chen related to mobile health technologies for lung function monitoring. He has published extensively in AJRCCM, JACI, JAMA, and Lancet Respiratory Medicine, with numerous studies featuring biostatisticians from Dr. Chen’s group as first or senior authors. His leadership roles include serving on the ATS Board of Directors and directing large pediatric asthma programs. Through his work, Dr. Forno exemplifies the highest standards of interdisciplinary and data-driven pediatric research.

Dr. Kathryn Torok is Associate Professor of Pediatrics at the University of Pittsburgh and Director of the Pediatric Systemic Scleroderma Center at UPMC Children’s Hospital of Pittsburgh. She is a nationally recognized leader in juvenile scleroderma, with deep expertise in clinical phenotyping, immunology, and translational research. Dr. Torok has partnered with Dr. Chen to pioneer multi-omic, single-cell, spatial analyses, and digital pathology in pediatric scleroderma. Supported by joint funding with Dr. Chen from NIH, DoD, and the Scleroderma Research Foundation, their team is generating the first and largest spatial transcriptomics atlas of the skin, with transformative insights into fibroblast–immune interactions and disease pathogenesis. Her longstanding clinical leadership and commitment to patient-centered research have enabled the generation of well-phenotyped cohorts, rich imaging datasets, and histologic resources that form the backbone of the team’s computational and statistical innovations. Dr. Torok’s collaborative vision has elevated pediatric scleroderma research into a model for cross-disciplinary team science.

Dr. Zhao Ren is Associate Professor of Statistics at the University of Pittsburgh and an expert in high-dimensional inference, graphical models, robust statistics, and statistical genomics. He serves as an Associate Editor for the Electronic Journal of Statistics, the Journal of Business & Economic Statistics, and Statistica Sinica. His methodological contributions span leading journals including the AoS, JASA, AoAS, JRSS-C, Bernoulli, Statistical Science, and PNAS. Dr. Ren plays a central role in the Chen Team by developing statistically rigorous frameworks for multi-omics integration, network modeling, and high-dimensional inference, including novel approaches for transcriptomic network analysis in childhood asthma. His collaborative work with Dr. Chen has led to influential publications in computational biology and applied genomics, including AoAS and PLOS Computational Biology. A dedicated mentor and educator, Dr. Ren has supervised numerous award-winning PhD trainees and serves as PI on multiple NIH- and NSF-funded projects. He brings indispensable quantitative depth to the team, ensuring methodological rigor and reproducibility across all analytic pipelines.

Dr. Molin Yue is a recent PhD graduate in Biostatistics from the University of Pittsburgh and is currently a Research Advisor in statistics at Eli Lilly and Company. His research focuses on multi-omics integration, deep learning, Gaussian graphical models, and asthma endotyping. Co-mentored by team member Drs. Chen, Ren, Forno, and Celedón, Dr. Yue has already emerged as an exceptional early-career statistical scientist. Dr. Yue is the first author of a landmark JAMA 2025 study demonstrating nasal transcriptomic endotypes of childhood asthma. He has also published in AJRCMB, AnnalsATS, Journal of Infection, Briefings in Bioinformatics, and Bioinformatics. His computational innovations include deep-learning fusion networks, deconvolution pipelines, and multi-modal prediction frameworks used across the team’s asthma, scleroderma, and infectious disease projects. He has received multiple ATS trainee awards, Biostatistics and School of Public Health research honors, and industry experience at Takeda Pharmaceuticals. Dr. Yue exemplifies the next generation of biostatistical leaders emerging from team science training.