Faculty Special Projects Fund

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 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.

Current request for proposals.



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)

Thwarting Malign State Attacks on Media in the Andean Region
Horacio Larreguy (Harvard Faculty of Arts and Sciences)



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)

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.