Student Paper Competition

Each year, SLDS hosts a student paper competition. Submission deadlines are typically December-January. Winners are announced in January, and awards are presented at the annual Joint Statistical Meetings. Details can be found on our announcements page. 

From over 79 submissions, the SLDS student paper competition committee has selected six winning papers (one under the applied track) and two honorable mentions that will be presented at the 2024 Joint Statistical Meetings in a contributed session (session name: "SLDS Student Paper Awards").  This promises to be a very interesting session, so we encourage JSM attendees to look out for this session in the program.

Student Paper Winners (in alphabetical order)

Name

Affiliation

Paper Title

Considine, Ellen

Harvard University

Optimizing Heat Alert Issuance for Public Health in the United States with Reinforcement Learning

Dharamshi, Ameer

University of Washington

Generalized Data Thinning Using Sufficient Statistics

Su, Buxin

University of Pennsylvania

The Exact Risk of Reference Panel-Based Regularized Estimators

Wen, Xin

Purdue University

Online Statistical Inference for Low-Rank Tensor Learning via Stochastic Gradient Descent

Wu, Shihao

University of Michigan

A General Latent Embedding Approach for Modeling High-Dimensional Hyperlinks

Zeng, Zhenghao

Carnegie Mellon University

Causal Inference with High-Dimensional Discrete Covariates

 

Honorable Mention

Tang, Runshi

University of Wisconsin-Madison

Mode-Wise Principal Subspace Pursuit and Matrix Spiked Covariance Model

Yu, Myeonghun

University of California, San Diego

Deep Neural Network Expected Shortfall Regression with Heavy-Tailed Data

 

We would like to thank the SLDS student paper competition committee members for their time, effort, and judgment in the selection process. We would not have been able to process such a large number of submissions without the generous contribution of all our committee members during the holiday season.

For questions, please contact the SLDS 2024 Student Paper Award Co-chairs, Kean Ming Tan (keanming@umich.edu) and Lingsong Zhang (lingsong@purdue.edu).


Previous winners are listed below:

2023 Winners

Name Affiliation Paper Title
Rungang Han University of Wisconsin-Madion Exact Clustering in Tensor Block Model: Statistical Optimality and Computational Limit
Peter MacDonald University of Michigan Latent space models for multiplex networks with shared structure
Tudor Manole Carnegie Mellon University Estimating the Number of Components in Finite Mixture Models via the Group-Sort-Fuse Procedure
Weijing Tang University of Michigan Population-level Balance in Signed Networks: A Latent Space Approach
Sheng Zhang North Carolina State University Distributed Community Detection in Large Networks


Honorable Mentions (in alphabetical order):

Name Affiliation Paper Title
Stefan Stein University of Warwick A Sparse Beta Model with Covariates for Networks
Xiaoqing Tan University of Pittsburgh A Tree-based Federated Learning Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources



2020 Winners

Student Paper Award Winners:
Name Affiliation Paper Title
Lucy Gao University of Washington Testing for Association in Multi-View Network Data
Weibin Mo University of North Carolina at Chapel Hill Learning Optimal Distributionally Robust Individualized Treatment Rules
Ilmun Kim Carnegie Mellon University Classification accuracy as a proxy for two-sample testing
Yiliang Zhang University of Pennsylvania High-Dimensional Nonparametric Density Estimation via Max-Random Forest
Xu Wang University of Washington Statistical Inference for Networks of High-Dimensional Point Processes
Honorable Mention:
Kenneth Tay Stanford University Reluctant additive modeling
Yinyin Chen University of Illinois at Urbana-Champaign Learning Topic Models: New Results on Identifiability and Consistency

 

2019 Winners

Student Paper Winners
Name Affiliation Paper Title
Yao Chen  Purdue University  Nonlinear Variable Selection via Deep Neural Networks
Zhengling Qi  University of North Carolina Chapel Hill  Estimating Individualized Decision Rules with Tail Controls
Michael Weylandt   Rice University Dynamic Visualization and Fast Computation for Convex Clustering via Algorithmic Regularization
Yubai Yuan University of Illinois Urbana-Champaign Community Detection with Dependent Connectivity
Yunfeng Zhang Texas  A&M University  Joint association and classification analysis of multi-view data
Honorable Mention
Jingyi Kenneth Tay  Stanford University  Principal component-guided sparse regression 



2018 Winners

Winner Affiliation    Paper Title
Boang Liu University of Michigan        Network augmented classification 
Hyebin Song University of Wisconsin PULasso: High-dimensional variable selection with presence-only data
Shuxiao Chen Cornell University Valid Inference Corrected for Outlier Removal
Fei Xue University of Illinois at Urbana-Champaign Variable Selection for Highly Correlated Predictors
Jean Feng University of Washington Sparse-Input Neural Networks for High-dimensional Nonparametric Regression and Classification




 2017 Winners

Winner Affiliation    Paper Title
Jianyu Liu         The University of North Carolina at Chapel Hill         Graph-based Sparse Linear Discriminant Analysis for High Dimensional Classification
Xin Qiu Columbia University Composite Interaction Tree for Robust Learning of Optimal Individualized Treatment Rules and Identifying Subgroups
Lauren N. Spirko Temple University Variable Selection for Large-Scale Genomic Data with Censored Survival Outcomes
Xiwei Tang University of Illinois Urbana-Champaign Individualized Multilayer Tensor Learning with An Application in Imaging Analysis
Yichen Zhang New York University Statistical Inference for Model Parameters in Stochastic Gradient Descent

 

 

2016 Winners

Winner Affiliation    Paper Title
Xuan Bi
  University of Illinois at Urbana-Champaign   A Group-Specific Recommender System
Boxiang Wang
  University of Minnesota   Another Look at DWD: Thrifty Algorithm and Bayes Risk Consistency in RKHS
Kevin Lee
  Pennsylvania State University   Model-Based Clustering for Large Scale Dynamic Networks
Hongyu Yang
  Massachusetts Institute of Technology   Scalable Rule Lists For Building Logical Classifiers
Yang Ni
 Rice University    Sparse Multi-dimensional Graphical Models: A Unified Bayesian Framework