The Harvard Data Science Initiative Faculty Special Projects Fund is intended to support one-time data science opportunities for which other funding is not readily available. Applications of up to $5000 are accepted on a rolling basis, and funding will be awarded throughout the year until available funding is exhausted. The total annual budget is $50,000.
2024
Project 42
Davide Viviano (Harvard Faculty of Arts and Sciences)
Project42 is a collective that fuses data science, music, and art. Number 42 evokes the popular random generation seed; as (data) science, music and art must be reproducible and shared.
Sensing the Landscape
Craig Douglas (Harvard Graduate School of Design)
This project explores the use of sensor networks to monitor and visualize atmospheric conditions at Harvard’s House Zero, creating innovative data-visualizations for public exhibition.
Affordable Housing Siting and Environmental Health Vulnerability: An Overview of 25 Years of the French SRU Law Model
Magda Maaoui (Harvard Graduate School of Design)
This data-visualization project seeks to map the evolution and distribution of affordable housing in France over the past two decades, focusing on how it intersects with environmental vulnerabilities.
A Large-Scale Analysis of P-Hacking
Sharad Goel (Harvard Kennedy School of Government)
Funding will enable the hiring of a research to validate the p-values collected and work to create a database along with collecting information on when the journals we are studying instituted data
sharing and preregistration policies.
Polinature: A plug in public space open data project
Belinda Tato (Harvard Graduate School of Design)
The grant will enable the creation of an open-source publication to share findings from the Polinature project, with the goal of making its benefits accessible to a wider audience.
Generative Causal AI for Alzheimer’s Disease Therapeutic Management
Junwei Lu (Harvard T.H. Chan School of Public Health)
Generative Learning: Interactive and Personalized Education with Generative AI Textbooks
Vijay Janapa Reddi (Harvard John A. Paulson School of Engineering and Applied Sciences)
Extracting novel computational biomarkers of anhedonia from neuroimaging data
Samuel Gershman (Harvard University Faculty of Arts & Sciences)
2023
Developing an Anomaly Detection Challenge for Time-domain Astrophysics
Ashley Villar (Harvard University Faculty of Arts & Sciences)
Starting in 2025, the Vera C. Rubin Observatory will lead a ten-year campaign to image the Southern Sky to unprecedented depth. In 2018, the Photometric LSST Astronomical Time-Series Classification Challenge (PLAsTiCC), a massive community-wide challenge was created to spur the development of classification algorithms for Rubin’s events. The aim of this project is to organize a three-day workshop at the Harvard Center for Astrophysics in February 2024, building on the successful PLAsTiCC challenge, to focus on anomaly detection in time-domain astrophysics using the upcoming Vera C. Rubin Observatory’s data. This workshop intends to bring together experts in astrophysics, AI, and Rubin infrastructure to design strategies for identifying rare transient events. It will involve talks, discussions, and collaborative hacking sessions, targeting early-career researchers and promoting engagement between domain experts and novices.
Machine Learning for Cultural Collections
David Alvarez-Melis and Alexandros Haridis (Harvard John A. Paulson School of Engineering and Applied Sciences)
Innovative Smartphone Application Tools for Public Health Justice
David Williams (Harvard T.H. Chan School of Public Health)
Development of a Data Analysis and Biostatistics Course for the Life Science Industry
Rafael Irizarry (Harvard T.H. Chan School of Public Health)
Astro AI
Douglas Finkbeiner (Harvard University Faculty of Arts & Sciences)
Clinical Decision Support Tool for Trans and Gender Diverse Patients on Hereditary Cancer Risk
Giovanni Parmigiani and Danielle Braun (Harvard T.H. Chan School of Public Health)
Textbook and community building initiative: How Artificial Intelligence can help to solve the world’s largest challenges
Weiwei Pan (Harvard John A. Paulson School of Engineering and Applied Sciences)
Machine Learning Journal Club
Douglas Finkbeiner (Harvard University Faculty of Arts & Sciences)
Historical Data and the Natural World: A Deep Dive into the Ukrainian Past
Serhii Plokhii (Harvard University Faculty of Arts & Sciences)
3D Motion Capture of Domestic Interactions for Kinetic Environments Design
Andrew Witt (Harvard Graduate School of Design)
Cosmic DS
Alyssa Goodman (Harvard University Faculty of Arts & Sciences)
Effect of household financial distress on children’s health
Margaret McConnell (Harvard T.H. Chan School of Public Health)
2022
TinyML Club
Vijay Janapa Reddi (Harvard John A. Paulson School of Engineering and Applied Sciences)
Interactive Black Lives Matter Street Mural Map Memetic Timeline
Jeffrey Schnapp (Harvard Faculty of Arts and Sciences)
Data Science Book Club
Kelly McConville(Harvard Faculty of Arts and Sciences)
The Constellations Project
Natalia Linos(Harvard T.H. Chan School of Public Health)
Workshop to Establish Collaborative Partnership for Costing Study of Innovative Digital Health Technology in Nigeria
Ryoko Sato (Harvard T.H. Chan School of Public Health)
Climate Change and Mental Health in Madagascar: A Health Systems Ecological Approach
Karestan Koenan (Harvard T.H. Chan School of Public Health)
Automated Captioning of Data Visualizations
Pavlos Protopapas (Harvard John A. Paulson School of Engineering and Applied Sciences)
2021
Advancing Data-Driven Scientific Discovery for Cross-Cultural Music Research
Steven Pinker (Harvard Faculty of Arts and Sciences)
A Toolkit for Precise Geographic Data on Urban Roads
Gabriel Kreindler (Harvard Faculty of Arts and Sciences)
The HDSI grant supported the creation of a toolkit for matching events with precise coordinates (such as accidents, speed cameras, etc.) to road segments from a base map (constructed from Open Street Map road segments). The toolkit and documentation are available here and here. This toolkit can be applied to other problems that require matching geographic events with road segments with a high degree of spatial precision.
The Opportunity Project @ Harvard
Jeffrey Schnapp (Harvard Faculty of Arts and Sciences)
In conjunction with the U.S. Census Bureau’s The Opportunity Project (TOP), teams of Harvard students joined a design sprint to develop projects using census data for public good. The TOP (at) Harvard sprint spanned the 2021 fall semester and was organized by metaLAB (at) Harvard.
The Amendments Project
Jill Lepore (Harvard Faculty of Arts and Sciences)
The Amendments Project aims to compile, classify, and analyze the text of proposed amendments to the U.S. Constitution from 1787 to the present in an online, searchable database, to be made available to the public, through an interactive website, and to scholars, through GitHub. An HDSI Special Projects award in 2021 provided crucial funding for advancing the collection and tagging of data and early work in visualizing the dataset; some preliminary representations were incorporated into a placeholder website, Amend, at http://amendmentsproject.org/.
2020
What do we know about police violence?
Adaner Usmani (Harvard Faculty of Arts and Sciences)
Leveraging Data Science to Inform Urban Public Transportation in the Wake of COVID-19: The Case of TransJakarta
Rema Hanna (Harvard Kennedy School)
Curatorial A(i)gents: AI interventions in Museum Collections
Jeffrey Schnapp (Harvard Faculty of Arts and Sciences)
Curatorial A(i)gents presented a series of machine-learning experiments with the Harvard Art Museums’ digital collections and data developed by members and affiliates of metaLAB (at) Harvard. The exhibition ran from March 1 through May 15, 2022 as part of an extended metaLAB residency in the Harvard Art Museums’ Lightbox Gallery.
Thwarting Malign State Attacks on Media in the Andean Region
Horacio Larreguy (Harvard Faculty of Arts and Sciences)
2019
Nutrition sensitive aquaculture in data-poor settings
Christopher Golden (Harvard T.H. Chan School of Public Health)
Semiotic GANs for Conceptual Exploration
K. Michael Hays (Harvard Graduate School of Design)
Teachly
Dan Levy (Harvard Kennedy School) and Theodore Svoronos (Harvard Kennedy School)
On the Representation of Reachable Spaces
Talia Konkle (Harvard Faculty of Arts and Sciences)
Theory of ML Seminar Series
Boaz Barak (Harvard John A. Paulson School of Engineering and Applied Sciences)
Data, Autocracy, and the Direction of Innovation
David Yang (Harvard Faculty of Arts and Sciences)
With the help of the HDSI Special Projects Grant, the project was able to recruit one extremely capable research assistant to help with cleaning the large datasets on Chinese AI firms and their software production, using NLP methods to categorize the software output, and conducting econometric analyses examine the role of government data in fostering AI firms’ innovation and product development.
Tax collection in Ghana dissemination
Anders Jensen (Harvard Kennedy School)
The DSI grant helped to finalize the initial analysis of the impacts of technology to strengthen the local property tax capacity in Ghana. The results of the study are suggestive that technology may have a potentially transformative role in improving local tax capacity in Ghana.
Deep Learning and Discovery in the Museum
Jeffrey Schnapp (Harvard Faculty of Arts and Sciences)
Educational videos explaining Urban Network Analysis tools for modeling pedestrian movement in cities.
Andres Sevtsuk (Harvard Graduate School of Design)
New research into the applications of tracking data in professional soccer
Mark Glickman (Harvard Faculty of Arts and Sciences) and Laurie Shaw (Harvard Faculty of Arts and Sciences)
Develop a normalized corpus of linguistic terms for the computational evaluation of formal relationships in design
Andrew Witt (Harvard Graduate School of Design)
Causal Inference Reading Group
Kosuke Imai (Harvard Faculty of Arts and Sciences), Marie-Abele Bind (Harvard Faculty of Arts and Sciences), Luke Miratrix (Harvard Graduate School of Education), Tyler VanderWeele (Harvard T.H. Chan School of Public Health), and Jose Zubizarreta (Harvard Medical School)
A roughly biweekly meeting which was held throughout the academic year. These meetings were attended by both faculty, graduate students, and postdocs. Discussions centered around recent papers and with outside scholars invited to present their work. The meetings helped facilitate networking and the exchange of methods across schools and research groups. In conjunction with the U.S. Census Bureau’s The Opportunity Project (TOP), teams of Harvard students joined a design sprint to develop projects using census data for public good. The TOP (at) Harvard sprint spanned the 2021 fall semester and was organized by metaLAB (at) Harvard.