2023

Registration for Spring 2023
Through February 24, 2023 Jones 222
Graduate registration for Spring 2023 runs from Monday, February 20th through noon, Friday, February 24th, 2023.

Student Seminar: JungHo Lee
3:30–4:00 pm Via Zoom
Master’s Thesis Presentation
JUNGHO LEE, Department of Statistics, The University of Chicago
“Extending Summability to Matrices”

Student Seminar: Taewan Kim
3:00–3:30 pm Via Zoom
Master’s Thesis Presentation
TAEWAN KIM, Department of Statistics, The University of Chicago
“Understanding the Transcriptional Regulation with 3D Genomic Structure”

Student Seminar: Gerald White
1:00–1:30 pm Via Zoom
Master’s Thesis Presentation
GERALD WHITE, Department of Statistics, The University of Chicago
“Exploring Denoising Autoencoder Architectures for Self-Supervised Learning”

Student Seminar: Sansen Wei
12:15–12:45 pm Via Zoom
Master’s Thesis Presentation
SANSEN WEI, Department of Statistics, The University of Chicago
“Structured Sparsity via the Generalized Elastic Net”

Student Seminar: Yunhong Wang
4:30–5:00 pm Via Zoom
Master’s Thesis Presentation
YUNHONG WANG, Department of Statistics, The University of Chicago
“Understanding the Sample Complexity of Offline Robust Reinforcement Learning With A General Uncertainty Set”

Student Seminar: Zilai Si
2:00–2:30 pm Jones 303
Master’s Thesis Presentation
ZILAI SI, Department of Statistics, The University of Chicago
“Path-Following in Bayesian Inference”

Student Seminar: Ilgee Hong
1:00–1:30 pm Via Zoom
Master’s Thesis Presentation
ILGEE HONG, Department of Statistics, The University of Chicago
“Simplified Framework for Contrastive Learning for Node Representations”

Student Seminar: Sowon Jeong
11:00–11:30 am Via Zoom
Master’s Thesis Presentation
SOWON JEONG, Department of Statistics, The University of Chicago
“Understanding Graph Neural Network as a Dimension Reduction Technique”

Student Seminar: Jake Singleton
10:00–10:30 am Jones 111
Master’s Thesis Presentation
JAKE SINGLETON, Department of Statistics, The University of Chicagoi
“Bayesian Bradley-Terry Models Infer Tennis Player Skills and Predict Tennis Match Results”