Dr. Buongiorno engages in transdisciplinary, computational research and specializes in the development of innovative and holistic problem-solving approaches. Her work involves combining multiple disciplines in order to generate new knowledge beyond the boundaries of individual fields.
At 蜜桃酱Guildhall, Dr. Buongiorno focuses on two main areas of research that aim to address large-scale problems. Her primary area of research uses human computation gaming to develop tools for fighting human trafficking using human-in-the-loop machine learning techniques. The second area of research revolves around the development of an autonomous agent system driven by large language models (LLMs) — a system that can be used to support research, automation, and a multitude of other activities.
Prior to her current position, Dr. Buongiorno served as a teaching fellow for "Foundations and Applications of Humanities Analytics" at the Santa Fe Institute (SFI) where she taught text mining concepts and methods. Additionally, she served as the technical lead for "Global Urbanization and Housing Affordability: Poverty, Property, and the City" at SMU. In this role, she designed tools and methods for the quantitative analysis of government data, including the United States Congressional Records and the historical 19th-Century Parliamentary Debates of Great Britain (also known as "Hansard"). Driven by her interest in designing computational systems to understand and address issues in our human past and present, she also contributed to various research efforts such as mining and producing data on The Legislative Council of Hong Kong (LegCo) and mapping historic labor movements in New York City.
Her work has been supported by the National Science Foundation (NSF), National Endowment of the Humanities (NEH), and the National Institute of Justice (NIJ).