2026
Student Seminar: Ryan Lin
4:00–4:30 pm Jones 111
Tuesday, May 5, 2026, at 4:00 PM, in Jones 111, 5747 S. Ellis Avenue
Master’s Thesis Presentation
Ryan Lin, Department of Statistics, The University of Chicago
“The Predictive Power of Multi-horizon Economic Forecasts—A SARIMAX Approach”
Student Seminar: Sihao Feng
3:30–4:00 pm Jones 111
Tuesday, May 5, 2026, at 3:30 PM, in Jones 111, 5747 S. Ellis Avenue
Master’s Thesis Presentation
Sihao Feng, Department of Statistics, The University of Chicago
“A Comparison of Mendelian Randomization Methods in the Presence of Pleiotropy”
Bahadur Memorial Lectures: Nancy Reid (Day 1)
11:30 am–12:30 pm Jones 303
Title: “Lies, Damned Lies, and Statistics”
Abstract: This is the title I used the first time I taught the U of T First-Year Seminar course, many years ago. I was nervous about the prospect of giving a seminar-style course for students fresh from high school, and unsure how to distinguish it from a run-of-the-mill introductory statistics course. As it turned out, however, the experience had a big impact on my teaching, research, and views on statistical science. Although much has changed in our field in the years since, the basic principles of reasoning with uncertainty have not. In this talk I will reflect on my experiences in trying to convey the ongoing importance of statistical science and perhaps hazard a guess about the future.
DSI Distinguished Speaker Series: Benjamin Recht
12:00–1:00 pm DSI 105
Benjamin Recht
Professor in the Department of Electrical Engineering and Computer Sciences
University of California, Berekley
Title: The Irrational Decision: How We Gave Computers the Power to Choose for Us
Abstract: Mathematicians and engineers of the 1940s set out to design machines capable of making critical decisions in the face of uncertainty. In less than a decade, they developed a suite of powerful mathematical technologies, including information theory, linear programming, game theory, and neural networks. These tools didn’t merely lay the foundation for contemporary computer science but became the foundation of a new definition of rationality itself, reshaping how we judge human decision making. The Irrational Decision traces how a computational framework designed for machines came to define rationality for people in economics, public policy, and popular culture.
This talk will explore success stories in accelerating computers, regulating pharmaceuticals, and deploying electronic commerce. The successes reveal a common pattern. Automated decision systems thrive in well-defined spaces with clear rules and measurable goals. However, the same systems produce results ranging from brittle to absurd outside those controlled settings. Given these strengths and limitations, the talk will close by asking how we can put these tools to work without surrendering human agency and judgment.
Student Seminar: Shangkai Zhu
9:00–9:30 am Jones 303
Friday, May 1, 2026, at 9:00 AM, in Jones 303, 5747 S. Ellis Avenue
Master’s Thesis Presentation
Shangkai Zhu, Department of Statistics, The University of Chicago
“$k$-Nearest Neighbors Probabilistic Conformal Prediction”
Student Seminar: Xiaolong Wang
9:00–9:30 am Jones 111
Wednesday, April 29, 2026, at 9:00 AM, in Jones 111, 5747 S. Ellis Avenue
Master’s Thesis Presentation
Xiaolong Wang, Department of Statistics, The University of Chicago
“Variational Inference for Mixed Infections”
Student Seminar: Yiwen (Evelyn) Zhao
3:30–4:00 pm Jones 111
Tuesday, April 28, 2026, at 3:30 PM, in Jones 111, 5747 S. Ellis Avenue
Master’s Thesis Presentation
Yiwen (Evelyn) Zhao, Department of Statistics, The University of Chicago
“Assessment of Fast-ADELLE, an efficient global testing method, with application to gene-level association analysis”
Statistics Colloquium: Stefan Wager
11:30 am–12:30 pm Jones 303
Stefan Wager
Department of Statistics
Stanford University
Title: Non-parametric Causal Inference in Dynamic Thresholding Designs
Abstract: Consider a setting where we regularly monitor patients’ fasting blood sugar, and declare them to have prediabetes (and encourage preventative care) if this number crosses a pre-specified threshold. The sharp, threshold-based treatment policy suggests that we should be able to estimate the long-term benefit of this preventative care by comparing the health trajectories of patients with blood sugar measurements right above and below the threshold. A naive regression-discontinuity analysis, however, is not applicable here, as it ignores the temporal dynamics of the problem where, e.g., a patient just below the threshold on one visit may become prediabetic (and receive treatment) following their next visit. Here, we study thresholding designs in general dynamic systems and show that simple reduced-form characterizations remain available for a relevant causal target, namely a dynamic marginal policy effect at the treatment threshold. We develop a local-linear-regression approach for estimation and inference of this estimand, and demonstrate promise of our approach in numerical experiments. Joint work with Aditya Ghosh.
Students Seminar: Kiho Park
1:00–3:00 pm Room 103
Thursday, April 23, 2026, at 1:00 PM, in Room 103, 5460 S University Ave.
Dissertation Defense Presentation
Kiho Park, Department of Statistics, The University of Chicago
“The Geometry of Concepts in Large Language Models”
Student Seminars: Sean O'Hagan
1:00–3:00 pm Jones 111
Wednesday, April 22, 2026, at 1:00 PM, in Jones 111, 5747 S. Ellis Ave.
Dissertation Defense Presentation
Sean O’Hagan, Department of Statistics, The University of Chicago
“Bayesian Nonparametric Learning and Uncertainty Quantification in the Age of Artificial Intelligence”