Suzanne Thornton

Education
PhD, Statistics, Rutgers University
BS, Statistics and Mathematics, University of Florida

Growing up, Suzanne Thornton’s family moved around a lot but eventually ended up in Lakeland, Florida, where she attended public school with her siblings. Although mathematically inclined from an early age, she remembers her frustration with gender bias in mathematics starting in grade school. Her early interest in mathematics was entertained mainly by men who were consistently surprised by her abilities and ultimately impressed upon her the belief women aren’t supposed to enjoy math. Fortunately, at the University of Florida, she attended huge introductory math courses in which the entire room was filled with a variety of students from all backgrounds and identities. In fact, her enjoyment of mathematics produced friendships from study groups. She and her classmates bonded while toiling over homework assignments and fondly recounting the quirky passion their professors had for theorems they did not yet fully understand.

Thornton’s statistical interest blossomed with her first course in mathematical statistics, during which she felt fortunate to have a professor who encouraged questions in class. Although she struggled with the material, her understanding grew throughout the semester. She began a small research project with that same professor, who ultimately encouraged her to consider graduate school, where she could continue to discover the beauty of statistics.

As a PhD student at Rutgers, Thornton studied under an adviser who fostered her confidence to publicly discuss statistical research and encouraged her participation at conferences. Not surprisingly, she found herself at JSM, where she discovered a program featuring a plethora of topics covering not just interesting research but also topics she, as a queer woman, had never felt welcome to discuss with her predominantly straight, male instructors.

The moment Thornton is proudest of in her career is a last-minute decision to attend a panel session on implicit bias. On this panel was Emma Benn, who courageously discussed her experiences as a Black, lesbian statistician. After waiting around to introduce herself and express gratitude for Benn’s work, Thornton received the warmest welcome from Benn, who immediately invited her to follow up with her. This impulsive decision ended up illuminating her path forward by introducing her to a newfound interest in statistical education and connecting her to a network of diverse statisticians.

Currently, Thornton’s general area of research concerns a special type of estimator called confidence distributions. Her work with confidence distributions focuses on new computational inference methods that connect different inferential paradigms. This is a small piece of a much larger effort by her PhD adviser and others to develop new methodologies to unify the foundational principles of statistical inference.

As a professor of statistics at Swarthmore, Thornton finds herself curious about the ways in which statistics education can be modernized and brought to a wider population. She thinks new perspectives offered by research such as this provide a great opportunity for statisticians to reimagine how they teach statistics to appeal to a broader audience and ultimately increase the diversity of the field.