$11 Million Grant Puts BIU Researchers at the Forefront of AI and Humanities Innovation

Two researchers from Bar-Ilan University have been selected among a small group of scholars worldwide to receive major funding through the Humanities and Artificial Intelligence (HAVI) program of Schmidt Sciences.

The nonprofit organization, founded by Eric Schmidt, is awarding a total of $11 million to up to 23 research teams globally. The initiative represents the first grant program of this scale dedicated specifically to applying artificial intelligence to the humanities, including history, philosophy, archaeology, art, and literature.

The two Bar-Ilan–affiliated projects come from independent research groups and span fields as different as medieval philosophy and mathematical art analysis, demonstrating the breadth of ways AI can deepen our understanding of human culture.

Tracing how ideas travel across centuries and cultures

Prof. Yehuda Halper, from Bar-Ilan University’s Department of Jewish Philosophy, is a co–principal investigator on the international project Connectivity and Individuality in Textual Traditions. The research team includes scholars from Harvard University, Columbia University, and Cornell University.

The project aims to build high-quality digital datasets in under-represented Eurasian languages and to develop AI tools capable of tracking how ideas move, transform, and are debated across time, geography, and intellectual traditions. By analyzing large bodies of historical texts, the researchers hope to reveal patterns of influence, disagreement, and continuity that would be impossible to detect manually.

All datasets and tools produced by the project will be released as open resources, supporting scholars worldwide in historical research, cultural preservation, and the development of more historically informed AI systems.

Prof. Halper’s own research focuses on medieval and Renaissance Jewish philosophy, particularly the ways Jewish thinkers engaged with Arabic, Greek, Latin, and Hebrew intellectual traditions. The project builds on digital critical editions he previously developed through Mahadurot: Modular Hebrew Digitally Rendered Texts, a platform designed to make complex textual traditions accessible for computational analysis.

Revealing hidden layers in art with mathematics and AI

Dr. Shira Faigenbaum-Golovin, from Bar-Ilan University’s Department of Mathematics, is leading a second HAVI-funded project in collaboration with a multidisciplinary team of researchers from universities and museums in the United States and Europe.

Her team is developing AI-driven methods to uncover hidden histories within artworks and cultural artifacts. By combining molecular imaging, spectroscopy, mathematical modeling, and machine learning, the researchers aim to virtually “unravel” layers of pigment in paintings and artifacts. This approach allows them to reconstruct original colors, model pigment degradation over time, and gain new insights into how artworks were created and altered across centuries.

The tools developed through the project are expected to support art restoration, attribution, and conservation, while also advancing AI techniques designed to work with complex, fragile, and incomplete historical data.

Building AI that understands the past

The Humanities and Artificial Intelligence program was created to address a central challenge in applying AI to the humanities: historical materials are often fragmented, multilingual, and shaped by cultural contexts that conventional AI systems struggle to interpret.

By supporting the development of historically aware AI, the HAVI program enables new forms of discovery, ranging from the analysis of ancient texts and lost archaeological sites to a deeper understanding of how technology, trade, and materials shaped art, literature, and human expression.

The selection of two Bar-Ilan University–led projects places the university at the center of a growing global effort to bridge cutting-edge artificial intelligence with the study of human history and culture, showing how advanced computation can illuminate the past rather than replace it.