天美传媒

Dr. Raphael Gottardo is a computational biologist who specializes in applying rapidly evolving ideas in data science to solving problems in cancer and related diseases. As scientific director of the Translational Data Science Integrated Research Center, he is at the center of the busy intersection of biology, data science and technology at Fred Hutchinson Cancer Research Center.

His goal is to expand data-driven innovations for patients by cultivating a cross-disciplinary environment in which doctors and laboratory scientists work seamlessly with their colleagues in biostatistics and computational sciences to take advantage of the flood of information made possible by advanced technologies. 

The aim is to bring scientific discoveries from research labs to the bedside sooner using data-driven approaches. To do so, bench scientists and clinical researchers from many corners of the Hutch work collaboratively with experts in data science.

Much of his work is focused on profiling the cellular components of the human immune system 鈥� using data science to understand how to make immunotherapies work better for patients. 

鈥淚t鈥檚 when you get into the details that it really becomes interesting,鈥� he said. 鈥淭he immune system is very complex, and it turns out we don鈥檛 know a whole lot about it yet. Looking at these single-cell technologies generating massive amounts of data has brought me to really cool statistical and computational challenges.鈥�

Dr. Gottardo鈥檚 own research involves the development of computational tools for vaccine and immunology studies, including high-throughput experiments that may use flow cytometry or high-speed genome sequencing. His current studies include:
鈥�	Statistical and computational analysis of flow cytometry data
鈥�	Development of statistical and computational methods for single-cell genomics
鈥�	Immune responses to malaria and HIV infection and immunization within the Human Immunology Project Consortium (HIPC)
鈥�	Development of the HIPC database and research portal (www.immunespace.org)
鈥�	Contribution to the Bioconductor project, an open computing resource for genomics
鈥�	Leadership for the Vaccine and Immunology Statistical Center of the Collaboration for AIDS Vaccine Discovery of the Bill and Melinda Gates Foundation
鈥�	Leadership for the Vaccine Statistical Support (VSS) Global Health Vaccine Accelerating Platform (GH-VAP) of the Bill and Melinda Gates Foundation

Dr. Gottardo is the J. Orin Edson Foundation Endowed Chair at Fred Hutch and a member of the Vaccine and Infectious Disease and Public Health Sciences Divisions. He, along with other Fred Hutch researchers, is co-leading a collaboration with the Allen Institute for Immunology to chart the human immune system by harnessing big data and emerging technologies.

An affiliate professor of statistics at the University of Washington, he teaches courses in stochastic modeling, bioinformatics and statistical computing and supervises biostatistics and statistics doctoral students on statistical-methods research for high-dimensional omics data analysis

Douglas C. Everett, PhD, is a researcher at National Jewish Health. Dr. Everett is in the Division of Biostatistics and Bioinformatics.

Education
1989	SUNY- Buffalo, PhD, Physiology
1983	Duke University, MS, Physical Therapy
1978	Cornell University, BA

Awards & Recognition
2006-Present: Associate Editor, Advances in Physiology Education
2001-Present: Editorial Review Board, Journal of Allergy and Clinical Immunology
2001-Present: Who's Who in America
2001-Present: International Directory of Distinguished Leadership
2001-2006: Editorial Review Board, Advances in Physiology Education
2002-2004: Cochair, Data and Safety Monitoring Committee, National Jewish Health

Professional Memberships
American Physiological Society
International Society on Oxygen Transport to Tissues
New York Academy of Sciences
American Statistical Association
International Society for Mountain Medicine

Dr. Bell鈥檚 research interests include examining the association of environmental exposures and adverse birth and child health outcomes, including neurodevelopment. She is particularly interested in the relationship between social factors and environmental exposures and their combined impact on child development. Dr. Bell most recently served as co-Principal Investigator of the Upstate KIDS study, a cohort study of over 6000 infants designed to examine risk factors for development differences, Autism and additional growth and developmental outcomes.

Currently, she is the co-Principal Investigator with the New York State Department of Health, of a cohort study to recruit and enroll participants into a prospective cohort of adults and children to examine the long-term health effects associated with consumption of drinking water contaminated with per and poly alkyl substances (PFAS).  She previously led the investigations of adverse reproductive outcomes by levels of air pollutants in the New York State Department of Health鈥檚 Environmental Health Tracking Program and previously served as a co-PI of the New York Center for the National Birth Defects Prevention Study/BD-STEPS multi-center studies funded by the Centers for Disease Prevention and Control (CDC).

Given the strong correlation between excess exposure to environmental contaminants, poverty and racial inequalities, her research and community service have more recently expanded into exploring the health outcomes related to these disparities. She currently serves on the executive committee of the Center for Social and Demographic Analysis and as a member of the Community Advisory Board for the Ezra Prentice neighborhood, an Environmental Justice Community in Albany, NY. She has previously served as a member on three of the Institute of Medicine Committees on Review of the Health Effects in Vietnam Veterans of Exposure to Herbicides. Currently, she is a member of the National Academy of Medicine's Committee on Guidance on PFAS Testing and Health Outcomes.

Dr. Erfani graduated from the School of Medicine at the National University of Iran, Tehran, Iran in 2014. He was offered a full scholarship to study MPH in 2013 and graduated from the School of Public Health in 2015. Seyed Hadi is currently a Post-doctoral Research Fellow in the Department of Obstetrics and Gynecology at the Baylor College of Medicine in Houston, Texas, where he is involved in multiple clinical, basic science and epidemiologic research projects related to Obstetrics and Gynecology and Maternal Fetal Medicine.

Dr. Zhang joined UT Southwestern as an assistant professor in September, 2007. He currently serves as the director of BERD (Biostatistics, Epidemiology, and Research Design) for the UTSW CTSA program. He also serves on the NCI Central Institutional Review Board (Adult CIRB – Early Phase Emphasis). 
Dr. Zhang’s research interest in statistical methodology lies in two main areas: Bayesian hierarchical modeling and clinical trial design. He has published multiple papers on the application of Bayesian hierarchical models to disease mapping, joint modeling of longitudinal and survival outcomes, item-response theory for grant review, functional enrichment analysis to detect important pathways, and multi-level modeling to detect factors that impact cancer screening, etc. Another area of his research interest is design methodology for clinical trials to account for various pragmatic issues such as correlated outcomes (clustered and longitudinal), missing data, small sample sizes, historical control, random variability in cluster size, and cost constraints, etc. He has published multiple high quality papers in this area and in 2015 he co-authored a book titled “Sample Size Calculations on Clustered and Longitudinal Outcomes in Clinical Research” (Chapman & Hall, New York). Dr. Zhang has been successful in securing extramural grants as the PI to support his independent research program, examples include an NIH R03 grant to conduct secondary data analysis on VA HIV registry; an NSF grant to build risk prediction model based on electronic health record data; and a PCORI methodology development grant to address pragmatic design issues in stepped-wedge cluster randomized trials.

Daniel J. Eck is a professor of statistics at the University of Illinois Urbana-Champaign. His research mission is to improve statistical methodologies that are applicable to real-world problems with a focus placed on both the theoretical and computational aspects of this methodology. To better understand relevant real-world problems, Eck works closely with scientists and researchers across a variety of disciplines. Eck's current methodological work has applications in evolutionary biology, baseball, history, education, epidemiology, and genomics studies. Eck teaches advanced statistical modeling, programming, and baseball analytics. He runs a joint internship with the Chicago Cubs in which undergraduate students get hands-on experience with baseball analytics in the real world.
Research interests

sports analytics
history
evolutionary biology
economics

Education
PhD Statistics, University of Minnesota, 2017
 BS Mathematics, Southern Illinois University Carbondale, 2009