I’m Bingxue, a fourth-year PhD candidate in Applied and Computational Mathematics and Statistics at the University of Notre Dame. Broadly, my research grows out of a problem that’s very common: statistical tools researchers use can behave inconsistently, and many powerful models are often too complex to explain how they reach a given conclusion. As more fields lean on these tools for downstream analysis, decision-making, and scientific discovery, this instability and opacity becomes a real risk.
My research focuses on developing statistical methodology that improves the stability and interpretability of the tools researchers already rely on. It’s work that people across many different fields can pick up and use. Part of my work is combining several ways of summarizing complex high-dimensional data. The idea is to build a single, more trustworthy visualization, since different methods often disagree about which patterns are reliable. I also work on turning powerful but not readily interpretable machine learning models into models simple enough for practitioners to understand and use, without losing much of the accuracy.
My work matters beyond statistics itself: it makes sure powerful data tools stay honest and understandable to people they actually affect. When practitioners use a model to help decide something important, like a medical diagnosis, they deserve to know why the model reaches that conclusion.
Can you tell us about your journey to graduate school at Notre Dame and what led you to apply to the Lucy Grad Scholars Program?
My journey started with seeing how researchers from different fields approach the same problem. In undergrad, I triple majored in physics, math, and statistics, with a minor in computer science. Working across these fields, I saw physicists focus on experiments and theory, mathematicians focus on proofs and numerical analysis, and computer scientists focus on implementing the algorithms. Statistics sits right in the middle, acting almost like a shared language that experimentalists, theorists, and engineers could all speak. This is exactly what motivated me toward graduate school and the Lucy Grad Scholars Program.
I like talking with peers from completely different fields and learning how the same problem can look entirely different through their eyes. This is what I like most about Lucy Grad Scholars Program: a group of scholars, each bringing a different lens, can together turn a narrow idea into something far more innovative and complete. In the long term, I would like to help build a stronger interdisciplinary graduate community at Notre Dame, a space where students from different departments regularly collaborate instead of working on their own.
How has the Lucy Family Institute contributed to your development as a researcher?
The Lucy Family Institute gives me regular exposure to research and challenges outside my own field, through seminars, presentations, and conversations with peers from all kinds of backgrounds. This has shaped my ability to think about the broader impact of my work and to communicate it well. Graduate students usually present to audiences within their own field, where we tend to lean on jargon without even noticing. Through the Lucy Grad Scholars Program, I’ve learned to communicate with peers across different disciplinary backgrounds instead. An important foundation of good collaboration is finding that shared language before diving into the work.
What projects are you involved in outside of your research at the Lucy Family Institute and/or the greater community?
Outside my own research, I’m involved with the Journal of Data and Societal Endeavors (JDSE), a student-led, peer-reviewed campus journal. Many students, especially undergraduates, complete strong work through a course project or thesis that is not quite ready for a formal journal or conference, and without an outlet, their work may never get publicly recognized. JDSE gives students a genuine venue to publish their work. Beyond providing the outlet, it also gives undergraduates a clear view of what the research process actually involves, including submission, review, and revision, which I think is more valuable than whether their work is accepted.
How do you spend your time beyond academic work?
Outside of work, I’m a big fan of mystery novels. I’ve read all of Agatha Christie’s books. My cat is even named Ellery, after Ellery Queen!