2022 Program for Women and Mathematics Explored Machine Learning
The 2022 Women and Mathematics (WAM) program took place from May 21–27, bringing together 40 students, educators, and researchers from universities around the world to participate in a series of lectures, problem sessions, research seminars, and special talks around the theme “The Mathematics of Machine Learning.” The program returned to campus for the first time since 2019 after being postponed in 2020 and held remotely in 2021.
The program’s Terng Lecture, named after Chuu-Lian Terng, past Member (1979, 1997–98) and one of the founders of WAM, was given by Cynthia Rudin of Duke University. The lecture, titled “Introduction to Interpretable Machine Learning,” unpacked the reputation of machine learning models as “black boxes,” offering the case that sophisticated algorithms can produce models that are interpretable by humans.
Maria Florina Balcan gave this year’s Uhlenbeck Lecture, named after current Distinguished Visiting Professor and founder of WAM Karen Uhlenbeck, titled “Foundations for Learning in the Age of Big Data.” In this lecture, Balcan described new models and algorithms for important emerging paradigms, specifically interactive learning and distributive learning.
Beginning as part of the Park City Mathematics Institute in 1993, WAM was established at IAS in 1994 under the leadership of Uhlenbeck and Terng, with support from then IAS Director Phillip Griffiths. Since then, it has dedicated itself to forming fruitful research relationships, encouraging a mentoring network in order to support women in mathematics, and countering the imbalance and attrition rate among female mathematicians compared to their male counterparts. In 2019, the program was recognized for its impact with the American Mathematical Society (AMS) “Mathematics Programs that Make a Difference” Award.
WAM continues its mission to recruit and retain more women in mathematics through new and sustained initiatives with the help of generous support from the National Science Foundation, Lisa Simonyi, and Princeton University Department of Mathematics.