2023
Student Seminar: Xingyue Fang
10:00–10:30 am Via Zoom
Master’s Thesis Presentation
XINGYUE FANG, Department of Statistics, The University of Chicago
“Study of geographical and demographic, and temporal factors affecting PM2.5 concentration level across the US”
Student Seminar: Simiao Jiao
4:30–5:00 pm Jones 111
Master’s Thesis Presentation
SIMIAO JIAO, Department of Statistics, The University of Chicago
“LU decomposition and Toeplitz decomposition of a neural network”
CAM Colloquium: Kui Ren
4:00–5:00 pm Jones 303
KUI REN, Department of Applied Physics & Applied Mathematics, Columbia University
“State-dependent Diffusion for Global Optimization”
Student Seminar: Yucong Liu
1:00–1:30 pm Jones 304
Master’s Thesis Presentation
YUCONG LIU, Department of Statistics, The University of Chicago
“LU decomposition and Toeplitz decomposition of a neural network”
CAM PhD Dissertation Defense: Yian Chen
3:00–4:00 pm Jones 303
YIAN CHEN, Computational and Applied Mathematics, University of Chicago
“Structured Low-complexity Matrix and Tensor Approximation with Applications”
CAM PhD Dissertation Defense: Yuming Chen
2:00–3:00 pm Jones 304
YUMING CHEN, Computational and Applied Mathematics, University of Chicago
“Data-driven Methods for Inverse Problems: Blending Data Assimilation and Machine Learning”
CAM PhD Dissertation Defense: Zehua Lai
5:00–6:00 pm Jones 226
ZEHUA LAI, Computational and Applied Mathematics, University of Chicago
“Algebraic and Differential Geometry in Modern Optimization”
Student Seminar: Yonghoon Lee
11:00 am–1:00 pm Jones 303
Dissertation Presentation and Defense
YONGHOON LEE, Department of Statistics, The University of Chicago
“Robust estimation and distribution-free inference for supervised learning”
Statistics Colloquium: Ruodu Wang
4:30–5:30 pm Jones 303
RUODU WANG, Department of Statistics and Actuarial Science, University of Waterloo
“E-backtesting”
CAM and Stats Student Seminar: Nathan Waniorek
12:30–1:30 pm Jones 226
NATHAN WANIOREK, Committee on Computational and Applied Mathematics, University of Chicago
“Analysis of a Computational Framework for Bayesian Inverse Problems”