Several faculty members in the Department of Mathematics were awarded National Science Foundation grants in 2024-25 for their innovative research and educational initiatives.
Associate Professor Calistus Ngonghala received a three-year NSF grant for his project “eMB: Collaborative Research: Integrated Hybrid Mathematical Modeling for Schistosomiasis Elimination.” This interdisciplinary collaboration with researchers at the University of Georgia and the University of Massachusetts focuses on the control and elimination of schistosomiasis, a neglected tropical disease caused by parasitic worms. The project aims to develop hybrid mathematical modeling tools to study how factors such as human mobility and environmental change influence disease dynamics in regions like Zanzibar and Ethiopia, with the goal of identifying effective and sustainable intervention strategies.
As part of this initiative, Professor Ngonghala organized a groundbreaking workshop in the summer of 2025 in Zanzibar, titled “Modeling Infectious Disease Transmission and Control with a Focus on Schistosomiasis.” This first-of-its-kind workshop in the country brought together scientists, students and public health professionals to equip a new generation of researchers and decision-makers with quantitative tools for understanding and combatting infectious diseases. Combining mathematical rigor with field-based learning, the program fostered collaborations across Africa, the U.S. and Thailand, while emphasizing the importance of connecting mathematical modeling with practical public health policy.
Professor Vincent Vatter was awarded a grant from the NSF Division of Undergraduate Education for his project, “Artificial Intelligence for Humanizing and Enhancing the Learning of Proofs.” As part of the Level II IUSE Engaged Student Learning track, this project explores how AI can improve undergraduate students’ proof-writing skills. The research investigates methods for providing students with timely, research-based feedback on their proofs and examines how AI can assist faculty in enhancing traditional teaching methods.
Professor Jindrich Zapletal received an NSF grant for his project “Choiceless Set Theory.” This research examines fundamental questions in set theory by studying mathematical structures without relying on the axiom of choice. Professor Zapletal has developed a novel method for classifying non-constructible objects — such as ultrafilters — by intuitive complexity across various mathematical domains. The project will produce an extensive chart of such objects and includes active involvement of graduate students.