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SPEAKERS
We are delighted to welcome speakers from Harvard, MIT, Microsoft Research New England, Netflix, data.org, Salesforce Research, and more!
Adam Tauman Kalai
Senior Principal Researcher, Microsoft Research New England
Workshop: Fairness and Explainability in AI
Workshop: Fairness and Explainability in AI
Amruta Nori-Sarma
Assistant Professor, Department of Environmental Health, Boston University School of Public Health
Panel 4: Data Science and Climate – Connecting planetary and human health
Panel 4: Data Science and Climate – Connecting planetary and human health
Arjun (Raj) Manrai
Assistant Professor of Biomedical Informatics, Harvard Medical School
Workshop: Fairness and Explainability in AI
Workshop: Fairness and Explainability in AI
Carolina Nobre
Assistant Professor in Computer Science, University of Toronto
Panel 1: Communicating Data Science – Trust with complexity
Panel 1: Communicating Data Science – Trust with complexity
Caroline Buckee
Professor of Epidemiology and Associate Director of the Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health
Panel 2: Impact Computing – Building an emerging field
Panel 2: Impact Computing – Building an emerging field
Damián Blasi
2020 Harvard Data Science Initiative Postdoctoral Fellow
Lightning Talks: HDSI Postdoctoral Fellows
Lightning Talks: HDSI Postdoctoral Fellows
Danil Mikhailov
Executive Director, data.org
Panel 2: Impact Computing – Building an emerging field
Panel 2: Impact Computing – Building an emerging field
David C. Parkes
HDSI Annual Conference 2022 Co-Chair
George F. Colony Professor of Computer Science, Harvard John A. Paulson School of Engineering and Applied Sciences; Faculty Co-Director, Harvard Data Science Initiative
Panel 3: Agent-Based Modeling – Complex ecosystems in silico
George F. Colony Professor of Computer Science, Harvard John A. Paulson School of Engineering and Applied Sciences; Faculty Co-Director, Harvard Data Science Initiative
Panel 3: Agent-Based Modeling – Complex ecosystems in silico
Esther Rolf
2022 Harvard Data Science Initiative Postdoctoral Fellow; Center for Research on Computation and Society (CRCS) Postdoctoral Fellow, Harvard John A. Paulson School of Engineering and Applied Sciences
Lightning Talks: HDSI Postdoctoral Fellows
Lightning Talks: HDSI Postdoctoral Fellows
Flavio du Pin Calmon
Assistant Professor of Electrical Engineering, Harvard John A. Paulson School of Engineering and Applied Sciences
Workshop: Fairness and Explainability in AI
Workshop: Fairness and Explainability in AI
Francesca Dominici
HDSI Annual Conference 2022 Co-Chair
Clarence James Gamble Professor of Biostatistics, Population and Data Science, Harvard T.H. Chan School of Public Health; Faculty Co-Director, Harvard Data Science Initiative
Panel 4: Data Science and Climate – Connecting planetary and human health
Clarence James Gamble Professor of Biostatistics, Population and Data Science, Harvard T.H. Chan School of Public Health; Faculty Co-Director, Harvard Data Science Initiative
Panel 4: Data Science and Climate – Connecting planetary and human health
George Dasoulas
2022 Wojcicki Troper Harvard Data Science Initiative Postdoctoral Fellow
Lightning Talks: HDSI Postdoctoral Fellows
Lightning Talks: HDSI Postdoctoral Fellows
Hanspeter Pfister
An Wang Professor of Computer Science, Harvard John A. Paulson School of Engineering and Applied Sciences
Panel 1: Communicating Data Science – Trust with complexity
Panel 1: Communicating Data Science – Trust with complexity
Himabindu Lakkaraju
Assistant Professor of Business Administration, Harvard Business School
Workshop: Fairness and Explainability in AI
Workshop: Fairness and Explainability in AI
Iavor I. Bojinov
HDSI Annual Conference 2022 Co-Chair
Assistant Professor of Business Administration, Harvard Business School; Richard Hodgson Fellow, Harvard Business School
Assistant Professor of Business Administration, Harvard Business School; Richard Hodgson Fellow, Harvard Business School
Irene Chen
ML/Statistics Postdoctoral Researcher, Microsoft Research New England; Incoming Assistant Professor, UC Berkeley and UCSF
Workshop: Fairness and Explainability in AI
Workshop: Fairness and Explainability in AI
Ivana Malenica
2022 Wojcicki Troper Harvard Data Science Initiative Postdoctoral Fellow
Lightning Talks: HDSI Postdoctoral Fellows
Lightning Talks: HDSI Postdoctoral Fellows
José R. Zubizarreta
Associate Professor, Department of Health Care Policy, Harvard Medical School; Associate Professor, Department of Biostatistics, Harvard School of Public Health; Faculty Affiliate, Department of Statistics, Harvard University
Tutorial: Causal Inference
Tutorial: Causal Inference
Joseph Dexter
2020 Harvard Data Science Initiative Postdoctoral Fellow
Lightning Talks: HDSI Postdoctoral Fellows
Lightning Talks: HDSI Postdoctoral Fellows
Karim R. Lakhani
Dorothy & Michael Hintze Professor of Business Administration, Harvard Business School
Introduction to Industry Keynote
Introduction to Industry Keynote
Lace Padilla
Assistant Professor, Cognitive and Information Sciences, University of California Merced
Panel 1: Communicating Data Science – Trust with complexity
Panel 1: Communicating Data Science – Trust with complexity
Maria De-Arteaga
Assistant Professor, McCombs School of Business, University of Texas at Austin
Academic Keynote
Academic Keynote
Marinka Zitnik
Assistant Professor of Biomedical Informatics, Harvard Medical School
Workshop: Fairness and Explainability in AI
Workshop: Fairness and Explainability in AI
Martin Tingley
Head of the Experimentation Platform Analysis Team; Netflix
Industry Keynote
Martin Tingley leads a multidisciplinary team on the Netflix Experimentation Platform, focused on developing and scaling both statistical methodology and software solutions to improve decision-making across the company. Prior to joining Netflix in 2017, Martin spent several years modeling and pricing catastrophe risk at Insurance Australia Group. In an earlier academic career, Martin was an Assistant Professor in Statistics and Meteorology at Penn State University. Martin holds a Ph.D. in Earth and Planetary Sciences and an M.A. in Statistics from Harvard University, and a B.Sc. in Physics from the University of Toronto.
Industry Keynote
Martin Tingley leads a multidisciplinary team on the Netflix Experimentation Platform, focused on developing and scaling both statistical methodology and software solutions to improve decision-making across the company. Prior to joining Netflix in 2017, Martin spent several years modeling and pricing catastrophe risk at Insurance Australia Group. In an earlier academic career, Martin was an Assistant Professor in Statistics and Meteorology at Penn State University. Martin holds a Ph.D. in Earth and Planetary Sciences and an M.A. in Statistics from Harvard University, and a B.Sc. in Physics from the University of Toronto.
Michael Norton
Harold M. Brierley Professor of Business Administration, Harvard Business School
Panel 3: Agent-Based Modeling – Complex ecosystems in silico
Panel 3: Agent-Based Modeling – Complex ecosystems in silico
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