Congratulations to the following University of Washington students who won best paper awards and honorable mentions in the 2025 American Statistical Association (ASA) student paper competitions. All are PhD students in Biostatistics in the School of Public Health.
Michael Hellstern received a best paper award and honorable mention for his poster in the Statistical Learning and Data Science Section. Hellstern’s paper,"Assumption-Lean Inference for Spectral Differential Network Analysis of High-Dimensional Time Series," highlights a method he and his collaborators developed to directly estimate and construct confidence intervals for a changing brain connectivity network. Their method allows for high-dimensional networks while requiring only mild assumptions. Hellstern collaborated with Ali Shojaie (advisor), Byol Kim, and Zaid Harchaoui.
Keshav Motwani received a best paper award from the Statistics in Imaging Section for his paper, "Disentangling Genetic Contributions to Human Brain Connectivity Using an Efficient Estimator of Variance Components in Multivariate Random Effects Models." Motwani and his collaborators developed an efficient method to disentangle and characterize genetic and environmental contributions to the network of neural connections in the human brain using magnetic resonance imaging data. This method is more broadly applicable to efficiently and accurately estimating and interpreting covariance structures that arise from multiple sources of variation in complex biological data. Motwani collaborated with Ali Shojaie, Ariel Rokem, and Eardi Lila.
Dwight Xu received a best paper award from the Section on Nonparametric Statistics His paper, "A Unified Framework for Semiparametrically Efficient Semi-Supervised Learning," provides a unified framework for valid and efficient statistical inference that incorporates additional unlabeled data when the number of labeled data is small. Xu’s work is jointly advised by Daniela Witten and Ali Shojaie.
Yuhan Qian received first place in the Biopharmaceutical Section for his paper, “From Estimands to Robust Inference of Treatment Effects in Platform Trials.” A platform trial is an innovative clinical trial design that uses a master protocol to evaluate multiple treatments in an ongoing manner, accelerating the evaluation of new treatments. Read more about his work.
Yinxiang Wu received the Distinguished Student Paper Award from the Section on Statistics in Genomics and Genetics for his work, “A More Credible Approach to Multivariable Mendelian Randomization.” Wu helped develop a novel method that enhances the reliability of analyses and introduced a general theoretical framework for more credible analysis of MVMR estimators. This research will help scientists better understand the causes of diseases and inform strategies for prevention and treatment. Read more about his work.
Albert Osom received an honorable mention for his paper in the Section on Risk Analysis titled "Developing Performance-Guaranteed Biomarker Combination Rules with Integrated External Information under Practical Constraints." The paper proposes an optimal biomarker-assisted decision rule designed to meet a pre-specified clinical utility constraint. This work is motivated by cancer screening applications, where the goal is to identify high-risk individuals who are most likely to benefit from further diagnostic evaluation, while avoiding unnecessary follow-up for those at lower risk. Osom's collaborators include his advisor Ying-Qi Zhao, as well as Ziding Feng and Camden Lopez.
Congratulations to all students for their outstanding work.
