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Student Seminar: Wufang Hong
2:00–2:30 pm Jones 111
Wednesday April 29, 2025, at 2:00 PM, in Jones 111, 5747 S. Ellis Avenue
Master’s Thesis l Presentation
Wufang Hong, Department of Statistics, The University of Chicago
“Empirical Partially Bayes Two Sample Testing”
Student Seminar: Juntao Mei
10:30–11:00 am Jones 303
Wednesday, April 30, 2025, at 10:30 AM, in Jones 303, 5747 S. Ellis Avenue
Master’s Thesis l Presentation
Juntao Mei, Department of Statistics, The University of Chicago
“TBA”
Student Seminar: Kiran Duggirala
11:00–11:30 am Jones 111
Wednesday April 30, 2025, at 11:00 AM, in Jones 111, 5747 S. Ellis Avenue
Master’s Thesis l Presentation
Kiran Duggirala, Department of Statistics, The University of Chicago
“Factor Augmented Time Series Approaches to Financial Forecasting Using Macroeconomic Data”
Student Seminar: Chin Howe Tsai
1:30–2:00 pm Jones 111
Wednesday April 30, 2025, at 1:30 PM, in Jones 111, 5747 S. Ellis Avenue
Master’s Thesis l Presentation
Chin Howe Tsai, Department of Statistics, The University of Chicago
“Predicting Aircraft Trajectory with Experimental Flight Data using Recurrent Neural Network”
Student Seminar: Lorenzo Rangone
3:00–4:00 pm Jones 111
Wednesday, April 30, 2025, at 3:00 PM, in Jones 111, 5747 S. Ellis Avenue
Master’s Thesis l Presentation
Lorenzo Rangone, Department of Statistics, The University of Chicago
“Combining Machine Learning and Data Assimilation Techniques for Moder Error Correction in Stochastic Dynamical Systems”
Student Seminar: Aditya Raman
3:30–4:00 pm Jones 111
Wednesday, April 30, 2025, at 3:30 PM, in Jones 111, 5747 S. Ellis Avenue
Master’s Thesis l Presentation
Aditya Raman, Department of Statistics, The University of Chicago
“Estimation of Approximately Sparse Covariance Operators for Multivariate Gaussian Processes”
Student Seminars: Yating Liu
10:00–11:00 am Jones 111
Thursday, May 1, 2025, at 10:00 AM, in Jones 111, 5747 S. Ellis Avenue
PhD Dissertation Proposal Presentation
Yating Liu, Department of Statistics, The University of Chicago
“High-Dimensional Inference Through Latent Structure”
Bahadur Memorial Lectures: John Lafferty (Day 2)
3:30–4:30 pm Jones 303
Title: Abstraction in Artificial and Natural Intelligence: Part II: Models, Mechanisms, and Experiments
Abstract: Reasoning in terms of relations, analogies, and abstraction is a hallmark of human intelligence. How can abstract symbols emerge from distributed, neural representations? One general approach uses an inductive bias for learning called the “relational bottleneck” that is motivated from principles of cognitive neuroscience. We present a framework that builds this inductive bias into machine learning models that transform distributed symbols to implement a form of abstraction. Computational experiments are presented on a broad range of problems. Biologically plausible mechanisms for these models are proposed to shed light on how abstraction may be implemented in the human brain.
Student Seminar: Mingkun Che
11:30 am–12:00 pm Jones 111
Friday, May 2, 2025, at 11:30 AM, in Jones 111, 5747 S. Ellis Avenue
Master’s Thesis l Presentation
Mingkun Che, Department of Statistics, The University of Chicago
“TBA”
Student Seminar: YingTing Lu
10:30–11:00 am Jones 111
Monday, May 5, 2025, at 10:30 AM, in Jones 111, 5747 S. Ellis Avenue
Master’s Thesis l Presentation
YingTing Lu, Department of Statistics, The University of Chicago
“Evaluating Hybrid Machine Learning Models for Time Series Forecasting”
Statistics Colloquium: Jiaying Gu
11:30 am–12:30 pm Jones 303
Jiaying Gu, Department of Economics, University of Toronto
Title: Empirical Bayes for Compound Adaptive Experiments
Abstract:
We investigate Empirical Bayes analysis in the context of compound adaptive experiments, where the arm distribution in each experiment follows a normal distribution with an unknown mean parameter that we aim to estimate. There are two primary approaches to EB estimation: g-modeling, which estimates the prior by maximizing the marginal likelihood, and f-modeling, which directly computes posterior means from the sample distribution of observations. We establish that g-modeling remains a valid EB procedure even when it incorrectly assumes exogenous data collection; it holds regardless of the sampling algorithm used and the endogeneity of sample sizes. One can apply standard g-modeling methods by treating the data as if it were exogenously sampled, and restrict attention to only the sample mean of the data. Remarkably, we show that the risk guarantees established for g-modeling with i.i.d data remain valid for adaptively generated data, with no need for prior knowledge of the sampling algorithm, even when it varies across experiments. In contrast, the f-modeling approach results in biased estimates. We validate the robustness of the g-modeling approach through simulations involving commonly used adaptive algorithms and illustrate its applicability using a real-world dataset comprising multiple sequential experiments.
Student Seminar: Yuchen Qiu
2:00–2:30 pm Jones 111
Monday, May 5, 2025, at 2:00 PM, in Jones 111, 5747 S. Ellis Avenue
Master’s Thesis l Presentation
Yuchen Qiu, Department of Statistics, The University of Chicago
“Pre- and Post- Error Behavior in a Sequential Learning Task”
Student Seminar: Evan Levine
2:30–3:00 pm Jones 111
Tuesday, May 6, 2025, at 2:30 PM, in Jones 111, 5747 S. Ellis Avenue
Master’s Thesis l Presentation
Evan Levine, Department of Statistics, The University of Chicago
“Bias-Adjusted Maximum Likelihood Estimators for LIMMA”
Student Seminar: Yunpeng Gao
3:00–3:30 pm Jones 111
Wednesday, May 7, 2025, at 3:00 PM, in Jones 111, 5747 S. Ellis Avenue
Master’s Thesis l Presentation
Yunpeng Gao, Department of Statistics, The University of Chicago
“Asymptotic Approximations of Forward Differences for the Densities of Sums of i.i.d. Random Variables”
Student Seminar: Robby Winter
12:00–12:30 pm Jones 111
Thursday, May 8, 2025, at 12:00 PM, in Jones 111, 5747 S. Ellis Avenue
Master’s Thesis l Presentation
Robby Winter, Department of Statistics, The University of Chicago
“TBA”
Billingsley Lectures on Probability: Nina Holden
3:30–5:00 pm Jones 303
We are pleased to have Prof. Nina Holden, Courant Institute of Mathematical Sciences, New York University, as our honored speaker on Thursday, May 8, 2025, at 3:30 PM, Jones 303, 5747 South Ellis Avenue. A reception will immediately follow the lecture at 5:20 pm, in the Stevanovich Center for Financial Mathematics, 5727 South University Avenue.
Title: Scaling limits of random planar maps
Abstract: Planar maps are graphs embedded in the sphere such that no two edges cross, where we view two planar maps as equivalent if we can get one from the other via a continuous deformation of the sphere. In this talk we will present scaling limit results (i.e., convergence results) for random planar maps and we will focus in particular on a notion of convergence known as convergence under conformal embedding.
Statistics Colloquium: Anne van Delft
11:30 am–12:30 pm Jones 303
Anne van Delft, Department of Statistics, Columbia University
“TBA”
2nd Year Mini Seminars
1:00–4:00 pm Social Sciences 108
Friday, May 16, 2025, from 1:00-4:30 PM, in Social Sciences 108, 1126 E. 59th St
Mini-Seminars for Second-Year PhDs
Moderator: Jimmy Lederman
1:00 pm: David Chen
1:15 pm: Minjun Cho
1:30 pm: Woohyun Choi
1:45 pm: Ankur Garg
2:00 pm: Junming Guan
2:15 pm: Qiyuan Liu
2:30 pm: Tannistha Mondal
2:45 pm: Beining Wu
3:00 pm: Zixuan Wu
3:15 pm: Dong Xie, Adaptive Confidence Interval with Contaminated Noise
Statistics Colloquium: Michael Hudgens
11:30 am–12:30 pm Jones 303
Michael Hudgens, Department of Biostatistics, University of North Carolina at Chapel Hill
“Causal Inference in Infectious Disease Prevention Studies”
Student Seminar: Ruiting Liang
12:30–1:00 pm Jones 111
Thursday, May 29, 2025, at 12:30 PM, in Jones 111, 5747 S. Ellis Avenue
Master’s Thesis l Presentation
Ruiting Liang, Department of Statistics, The University of Chicago
“TBA”
Student Seminar: Melissa Adrian
10:00 am–12:00 pm Jones 304
Thursday, June 26, 2025, at 10:00 AM, in Jones 304, 5747 S. Ellis Avenue
PhD Dissertation Defense Presentation
Melissa Adrian, Department of Statistics, The University of Chicago
“TBA”