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Jalees Rehman is a professor of Medicine, Pharmacology and Biomedical Engineering at University of Illinois, College of Medicine. His laboratory investigates inflammation and immune responses to pathogens as well as the resolution of tissue injury using mechanistic molecular approaches, experimental disease models and novel computational approaches. One example is the development of a machine learning approach to infer the activity of transcription factors using single cell RNA-seq data and prior knowledge gleaned from ChIP-seq data. Understanding the dynamics of physiological and pathophysiological gene expression networks can help distinguish adaptive (“healthy”) and maladaptive (“unhealthy” or “excessive”) responses to stressors. He is a Fellow of the American Heart Association, and an Elected Member of the American Society for Clinical Investigation. Jalees went to medical school at the Technische Universität München in Munich, Germany. He also completed clinical training as a cardiologist and postdoctoral training in vascular regeneration as part of a physician scientist track at Indiana University, School of Medicine. http://mcph.uic.edu/rehman/ and https://twitter.com/jalees_rehman.
Sandrine Dudoit is Professor and Chair of the Department of Statistics and Professor in the Division of Biostatistics, School of Public Health, at the University of California, Berkeley. Professor Dudoit’s methodological research interests regard high-dimensional inference and include exploratory data analysis (EDA), visualization, loss-based estimation with cross-validation (e.g., density estimation, classification, regression, model selection), and multiple hypothesis testing. Much of her methodological work is motivated by statistical inference questions arising in biological research and, in particular, the design and analysis of high-throughput microarray and sequencing gene expression experiments, e.g., single-cell transcriptome sequencing (RNA-Seq) for discovering novel cell types and for the study of stem cell differentiation. Her contributions include exploratory data analysis, normalization and expression quantitation, differential expression analysis, class discovery, prediction, inference of cell lineages, and integration of biological annotation metadata (e.g., Gene Ontology (GO) annotation). She is also interested in statistical computing and, in particular, reproducible research. She is a founding core developer of the Bioconductor project. https://www.stat.berkeley.edu/~sandrine/ and https://twitter.com/cendrinou.
Mine Çetinkaya-Rundel is Professor of the Practice and the Director of Undergraduate Studies at the Department of Statistical Science and an affiliated faculty in the Computational Media, Arts, and Cultures program at Duke University as well as Developer Educator at RStudio. Mine works on innovation in statistics and data science pedagogy, with an emphasis on computing, reproducible research, student-centered learning, and open-source education. At RStudio, Mine’s work focuses primarily on education for open-source R packages as well as building resources and tools for educators teaching statistics and data science with R and RStudio. Mine has authored four undergraduate statistics textbooks as part of the OpenIntro projects, teaches the popular MOOC Statistics with R on Coursera and is the developer and maintainer of Data Science in a Box. Mine is a Fellow of the ASA and an Elected Member of the ISI as well as the recipient of the 2021 Robert V. Hogg Award For Excellence in Teaching Introductory Statistics, the 2018 Harvard Pickard Award, and the 2016 ASA Waller Education Award. https://mine-cr.com/ and https://twitter.com/minebocek.
Bhramar Mukherjee is Professor and Chair of the Biostatistics Department at the University of Michigan. Her research group develops novel inferential methods for epidemiological data using Bayesian, frequentist and hybrid methods. She is especially interested in how environmental exposures contribute to disease, and their interactions with genotype. Since the COVID-19 pandemic began, she has contributed to epidemiological understanding of it with publications that have estimated real-world vaccine efficacy in Michigan, and the epidemiological trajectory in India. For this, she has been quoted extensively in the national and international news media. Dr. Mukherjee has served in editorial roles for numerous biomedical journals including Biometrics, and Statistics in Medicine. She has also been elected Fellow in the American Statistical Association and the American Association for the Advancement of Science. https://sph.umich.edu/faculty-profiles/mukherjee-bhramar.html and https://twitter.com/BhramarBioStat.
Dr. Furlan studies the biology of blood stem cell transplantation and cellular immunotherapy for people with cancers and other diseases. He is learning how immune cells, such as T cells, behave during and after treatment, and how changes in immune cell behavior affect treatment outcomes. He aims to use what he learns to improve transplantation and T-cell therapies for children. Dr. Furlan employs a method called single-cell genomics, which reveals an unprecedented level of detail about the individual cells in a sample. This technique shows him how immune cells respond to new biological surroundings, or microenvironments, throughout treatment. One particular research focus is immune dysfunction in graft-vs.-host disease, in which transplanted donor immune cells attack a patient’s healthy tissues. He also focuses on learning how to improve T-cell therapy and how transplanted donor immune cells affect cancers. https://www.fredhutch.org/en/faculty-lab-directory/furlan-scott.html and https://mcb-seattle.edu/faculty-profile/?uid=362.
Amy Willis is the Principal Investigator of the Statistical Diversity Lab and a tenure-track Assistant Professor in the Department of Biostatistics at the University of Washington. Amy and the StatDivLab develop tools for the analysis of microbiome and biodiversity data. Amy is passionate about reproducible science, meaningful data analysis, ecosystem and host health, and collaborating with scientists who share these values. Amy is the recipient of a NIH Outstanding Investigator Award, and a University of Washington Outstanding Faculty Mentor Award. http://statisticaldiversitylab.com/team/amy-willis, https://twitter.com/AmyDWillis, and http://faculty.washington.edu/adwillis/cv-website.pdf.
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