Our Data Science Zoominars feature interactive conversation with #datascience experts and a live Q+A session moderated by faculty at the Department of Data Science at Dana-Farber Cancer Institute.
Daniela Witten, PhD - The Role of Statistical Learning in Applied Statistics
What is machine learning? What distinguishes it from statistics? Daniela Witten, PhD is Professor of Statistics and Biostatistics at University of Washington, and the Dorothy Gilford Endowed Chair in Mathematical Statistics. Dr. Witten develops statistical machine learning methods for high-dimensional data, with a focus on unsupervised learning.
Our Data Science Zoominars feature interactive conversation with data science experts and a Q+A session moderated by Rafael A. Irizarry, PhD, Chair, Department of Data Science at Dana-Farber Cancer Institute.
15 May 2022
Elisabeth Bik, PhD - The Prevalence of Inappropriate Image Duplication in Research Publications
How prevalent is image alteration in biomedical research publications? What counts as manipulation? Elisabeth Bik, PhD, Principal at Harbers Bik, LLC, is a science consultant and microbiome, science integrity and image forensics expert.
Our Data Science Zoominars feature interactive conversation with data science experts and a Q+A session moderated by Rafael A. Irizarry, PhD, Chair, Department of Data Science at Dana-Farber Cancer Institute.
15 May 2022
Jeff Leek, PhD - Teaching Data Science to the Masses
How should we teach data science? Jeff Leek, PhD is a Professor at the Johns Hopkins School of Public Health, co-editor of Simply Statistics, co-director of the Johns Hopkins Data Science Lab and co-founder of Problem Forward Data Science.
Our Data Science Zoominars feature interactive conversation with data science experts and a Q+A session moderated by Rafael A. Irizarry, PhD, Chair, Department of Data Science at Dana-Farber Cancer Institute.
13 May 2022
Alberto Cairo, PhD - Data Visualization Literacy
How can we best communicate our data science findings using #dataviz? Alberto Cairo, PhD is a journalist, designer, and the Knight Chair in Visual Journalism at the School of Communication of the University of Miami (UM). He is the author of How Charts Lie, The Truthful Art, The Functional Art, and Nerd Journalism. He is also the director of the visualization program at UM’s Center for Computational Science.
Our Data Science Zoominars feature interactive conversation with data science experts and a Q+A session moderated by Rafael A. Irizarry, PhD, Chair, Department of Data Science at Dana-Farber Cancer Institute.
12 May 2022
Arnaldo Cruz, MPP - Data-Driven Policy in Puerto Rico
How does data transform policy making? Arnaldo and Rafa discuss the importance of data-driven decisions in governance and the state of data in PuertoRico.
For the past 17 years, Arnaldo Cruz has worked for the government, private and nonprofit sectors, focused in analytics, program evaluation, finance, and information technology. He is currently the Director of Research and Policy of the Financial Oversight and Management Board of Puerto Rico. the Office of Management and Budget at the City of Chicago, and several other organizations. Arnaldo is co-founder of ABRE Puerto Rico, an organization dedicated to promoting data driven decisions in Puerto Rico. He has also worked for the US Census, the Mayor’s Office of Workforce Development, he was chairman of the board of the Puerto Rico Institute of Statistics, the government entity in charge of establishing the statistical policy for the Commonwealth and is an adjunct professor at Sacred Heart University College of Business. Arnaldo has a Masters in Public Policy, from the Harris School of Public Policy Studies at the University of Chicago.
Our Data Science Zoominars feature interactive conversation with data science experts and a Q+A session moderated by Rafael A. Irizarry, PhD, Chair, Department of Data Science at Dana-Farber Cancer Institute.
11 May 2022
Andrew Gelman, PhD - Election Forecasting
How is statistics used to predict elections? Andrew and Rafa discuss the U.S. 2020 Election and the role of the electoral college, polls, mail-in ballots and voter data in forecasting results and post-election outcomes.
Andrew Gelman, PhD is a professor of statistics and political science at Columbia University. He is one of the go-to statisticians for the New York Times and author of perhaps the most popular statistics blog: Statistical Modeling, Causal Inference, and Social Science. He has received the Outstanding Statistical Application award three times from the American Statistical Association, the award for best article published in the American Political Science Review, and the Council of Presidents of Statistical Societies award for outstanding contributions by a person under the age of 40. Books he has authored and co-authored include Bayesian Data Analysis, Teaching Statistics: A Bag of Tricks, Data Analysis Using Regression and Multilevel/Hierarchical Models, Red State, Blue State, Rich State, Poor State: Why Americans Vote the Way They Do, A Quantitative Tour of the Social Sciences, and Regression and Other Stories.
Our Data Science Zoominars feature interactive conversation with data science experts and a Q+A session moderated by Rafael A. Irizarry, PhD, Chair, Department of Data Science at Dana-Farber Cancer Institute.
10 May 2022
Emma Benn, DrPH - Increasing Diversity in Data Science
What do we mean by diversity in STEM and why is it important? What works and what doesn't to increase diversity in data science?
Emma K. T. Benn, DrPH, MPH is Associate Professor in the Center for Biostatistics and Department of Population Health Science and Policy at the Icahn School of Medicine at Mount Sinai. Her recent focus is on applying statistical expertise to health disparities research. Full bio: https://www.mountsinai.org/profiles/emma-k-benn.
Our Data Science Zoominars feature interactive conversation with data science experts and a Q+A session moderated by Rafael A. Irizarry, PhD, Chair, Department of Data Science at Dana-Farber Cancer Institute.
9 May 2022
Sir David Spiegelhalter, PhD - Communicating Statistical Findings Effectively
What does the future hold for statistics education? How can we improve public data literacy? Professor Sir David Spiegelhalter, PhD is Chair of the Winton Centre for Risk and Evidence Communication at University of Cambridge, dedicated to improving the way that quantitative evidence is used in society. He has been an applied statistician for over 40 decades and has been involved in several projects with important implications. His academic work has focused in Bayesian statistics, including being co-developer of BUGS and winBUGS, biomedical applications and science communication. He has won numerous awards for his work including being knighted in 2014. He is the author of a very popular book The Art of Statistics, Learning from Data.
Our Data Science Zoominars feature interactive conversation with data science experts and a Q+A session moderated by Rafael A. Irizarry, PhD, Chair, Department of Data Science at Dana-Farber Cancer Institute.
8 May 2022
F. DuBois Bowman, PhD - Data Science and Academic Leadership
What's it really like to be a dean? How do academic administrators use data collection and analysis to guide decisions?
A renowned expert in the statistical analysis of brain imaging data, F. DuBois Bowman, PhD, is dean of the University of Michigan School of Public Health, one of the nation’s top public health programs. Dr. Bowman’s work mines massive data sets and has important implications for mental and neurological disorders such as Parkinson’s disease, Alzheimer’s disease, depression, schizophrenia, and substance addiction. His research has helped reveal brain patterns that reflect disruption from psychiatric diseases, detect biomarkers for neurological diseases, and determine more individualized therapeutic treatments.
Our Data Science Zoominars feature interactive conversation with data science experts and a Q+A session moderated by Rafael A. Irizarry, PhD, Chair, Department of Data Science at Dana-Farber Cancer Institute.
7 May 2022
Timothy Rebbeck, PhD - The Importance of Representative Samples in Clinical Trials
While we do cancer clinical trials to test drugs, exposures that increase risks are found with observational studies. These have also been instrumental in highlighting disparities. Tim Rebbeck and Rafa Irizarry discuss the challenges these studies pose.
Timothy Rebbeck, PhD is the Vincent L. Gregory, Jr. Professor of Cancer Prevention at the Harvard TH Chan School of Public Health and Professor of Medical Oncology at the Dana-Farber Cancer Institute. Dr. Rebbeck’s research focuses on the etiology and prevention of cancer, with an emphasis on cancers with a genetic etiology and those that are associated with disparities in incidence or mortality by race. He has directed multiple large molecular epidemiologic studies and international consortia that have been used to identify and characterize genes involved in cancer etiology, understand the relationship of allelic variation with biochemical or physiological traits, explore interactions of inherited and somatic genomic variation with epidemiological risk factors.
Our Data Science Zoominars feature interactive conversation with data science experts and a Q+A session moderated by Rafael A. Irizarry, PhD, Chair, Department of Data Science at Dana-Farber Cancer Institute.
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