2023
Student Seminar: Wei Kuang
3:00–4:00 pm Via Zoom
Dissertation Proposal Presentation
WEI KUANG, Department of Statistics, The University of Chicago
“Statistical Inference for Inexact Stochastic Newton Algorithm”
Student Seminar: Huy Dang Tran
11:00 am–12:30 pm Jones 303
Dissertation Proposal Presentation
HUY DANG TRAN, Department of Statistics, The University of Chicago
“New Methodologies for High-Dimensional Data Under Structured Sparsity”
Statistics Colloquium: Russell Lyons
4:30–5:30 pm Math/Stat 112
BILLINGSLEY LECTURES ON PROBABILITY
RUSSELL LYONS, Department of Mathematics, Indiana University
“Voronoi Tessellations without Nuclei”
CAM Colloquium: Chi-Kwong Li
3:00–4:00 pm Jones 303
CHI-KWONG LI, Department of Mathematics, College of William and Mary & Institute for Quantum Computing, University of Waterloo
“Some Recent Results in Quantum Tomography”
Student Seminar: Irina Cristali
2:30–4:00 pm Jones 304
Dissertation Proposal Presentation
IRINA CRISTALI, Department of Statistics, The University of Chicago
“Two Applications of Machine Learning: Causally Estimating Peer Influence on Networks and Learning Concepts from Text and Images”
Statistics Colloquium: Peng Ding
4:30–5:30 pm Jones 303
PENG DING, Department of Statistics, University of California Berkeley
“Interpretable sensitivity analysis for the Baron–Kenny approach to mediation with unmeasured confounding”
CAM Colloquium: Rachel Ward
4:00–5:00 pm Jones 303
Joint Colloquium with The Data Science Institute
RACHEL WARD, Oden Institute for Computational Engineering & Sciences, Department of Mathematics, The University of Texas at Austin
“Gradient Descent for Low-Rank Matrix Factorization”
CAM PhD Dissertation Defense: Solomon Quinn
3:00–4:00 pm Jones 303
CAM PhD Dissertation Defense
SOLOMON QUINN, Computational and Applied Mathematics, University of Chicago
“Asymmetric Transport in Continuous Topological Insulators”
Statistics Colloquium: Johannes Schmidt-Hieber
4:30–5:30 pm Jones 303
JOHANNES SCHMIDT-HIEBER, Department of Statistics, University of Twente
“Statistical learning in biological neural networks”