Emily L. Spratt is a Post-Doctoral Research Fellow in the Data Science Institute in collaboration with the Historic Preservation Program in the Graduate School of Architecture, Planning and Preservation and the Department of Computer Science in the School of Engineering and Applied Science. Emily is investigating the development of AI-enhanced technologies for the analysis, generation, and curation of art and architecture, the ethics surrounding this subject, and the philosophical and legal implications of the use of digital images in our society. Emily received her Ph.D. from Princeton University in the Department of Art and Archaeology and wrote her dissertation on the visual culture of Byzantium across the Venetian, Ottoman, and Slavic territories of the early modern world. She also holds an M.A. in Renaissance art history from Princeton, an M.A. in Byzantine art history from the University of California, Los Angeles, and a B.A. in art history, religious studies, and psychology from Cornell University. Previously, Emily worked as a strategic advisor in the art market and art-tech industry, and also has international curatorial experience in the museum and cultural heritage sector. Emily has taught in the Department of Art History and the Cultural Heritage and Preservation Studies program at Rutgers University, where she also was a member of the Art and AI Laboratory in the Department of Computer Science and the curator of the AI art collection. At Columbia, she is a member of the Preservation Technology Laboratory and the Computer Vision Laboratory, and is leading an extramural collaborative research project on the ethics of technology and facial recognition systems.

Emily has been the recipient of numerous fellowships and awards, including those from the Onassis Foundation, the Gladys Krieble Delmas Foundation, the Cini Foundation in Venice, the Cyprus American Archaeological Research Institution, the American Research Center in Sofia, Bulgaria, the Hellenic Ministry of Culture, the Frick Collection and Art Reference Library, and the universities from where she obtained degrees. Additionally, she holds several advisory positions in academia, government, and industry, and actively sources, evaluates, and consults on machine learning-related companies.