Since its launch in 2017, the HDSI has worked across Harvard to unite leading computer scientists, statisticians, and domain experts from law, business, public policy, education, medicine, public health, and myriad academic disciplines to derive meaningful and actionable insights that shape the new science of data. Its research drives data-driven policy and analyzes implications of big data for human society.
In academic year 2021/2022 we look forward to hosting seminars, panels, tutorials, workshops, and networking events to celebrate Harvard's data science community, our researchers' advances in methodologies and applications, and our broader impact outside of Harvard's walls.
We hope you'll join us.
As an open access platform of the Harvard Data Science Initiative, the Harvard Data Science Review features foundational thinking, research milestones, educational innovations, and major applications, with a primary emphasis on reproducibility, replicability, and readability. It aims to publish contents that help to define and shape data science as a scientifically rigorous and globally impactful multidisciplinary field based on the principled and purposed production, processing, parsing and analysis of data. By uniting the strengths of a premier research journal, a cutting-edge educational publication, and a popular magazine, HDSR provides a crossroads at which fundamental data science research and education intersect directly with societally-important applications from industry, governments, NGOs, and others. By disseminating inspiring, informative, and intriguing articles and media materials, HDSR aspires to be a global forum on everything data science and data science for everyone.
HDSI BY THE NUMBERS
The Harvard Data Science Initiative Postdoctoral Fellows are outstanding early-career researchers whose interests lie in a number of different fields. HDSI Fellows work independently over a two- to three-year fellowship with the guidance and partnership of Harvard University faculty.
RESEARCH PROGRAM HIGHLIGHTS
In 2020/2021, the Harvard Data Science Initiative launched three major research programs. These programs - Causal Inference, Trust in Science, and Bias2 - build upon our bedrock of strength in computer science, statistics, and the liberal arts. Each program features community-building activity, funding for cutting edge research, and a commitment to translating new knowledge into real-world impact.
All of the HDSI's activities leverage ongoing work in five thematic pillars: Data-Driven Scientific Discovery, Personalized Health, Networks & Markets, Evidence-Based Policy, and Methdology.
TRUST IN SCIENCE
With support from the Alfred P. Sloan Foundation, the Harvard Data Science Initiative supports a three-part project on Causal Inference for Complex Treatment Regimes. The Project takes aim at three specific roadblocks that stand between prediction and causation: experimental design; spillover effects; and addressing heterogeneity.
Trust in Science is a flagship project of the Harvard Data Science Initiative conducted in collaboration with the Harvard Kennedy School's Program on Science, Technology & Society (STS). The Project leverages data science, science and technology studies, and related disciplines to analyze the breakdowns in public trust, and to ask what steps could be taken to promote better mutual understanding.
Launched in September 2020, the Bias2 Program supports research, features speakers, and engages thedata science community towards using data science to uncover bias and improve decision making, and understanding and combating the use of badly-conceived data science that reinforces inequity. Bias2 ispart of the HDSI’s larger efforts to address the structures in our field that reinforce systemic racism.
Managing Director, HDSR
Director of External Engagement
Assistant Director, Programs and Operations
Engagement and Events Coordinator
Editorial Assistant, HDSR