NESS Student Research Awards 2023

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NESS Student Research Awards have a long history. The winners will be selected by the NESS Student Research Awards committee based on the overall quality of the research, and they will be acknowledged at the symposium and will receive a plaque in honor of their accomplishments. Please note that award winners from previous years are not eligible for another award.

Submission information for the 36th New England Statistics Symposium can be found here: https://symposium.nestat.org/awards.html.


Student Research Awards

Year

Sponsor

Award Committee

Recipient(s)
2023 MassMutual Gina Peloso (Co-Chair), Yang Lin (Co-Chair), Marie-Abele C Bind, Lelys Bravo de Guenni, Howard Cabral, Ming-Hui Chen, Seung Hoan Choi, Akshunna S. Dogra, Jeremy Gaskins, Nadeesha Jayaweera, Sayar Karmakar, Chi Hyun Lee, Jung Wun Lee, Xihao Li, Xinyi Li, Austin Menger, Paula Moraga, Heather Shappell, Neil Spencer, Emily Patricia Stephen, Steffen Ventz, Wei Wang, Ce Yang, Alex Young, Xiaonan Zhu, Beth Ziniti . [contact] Alan N. Amin, Di Wang, Gary Hettinger, Jing Wang, Kaidi Kang, Penghui Huang, Tianle Liu, Ye Tian

Sorted by year and student last name

Year

Student

University

Paper Title
2023 Alan N. Amin Harvard University Biological Sequence Kernels with Guaranteed Flexibility
2023 Di Wang University of Michigan Incorporating External Risk Information with the Cox Model under Population Heterogeneity: Applications to Trans-Ancestry Polygenic Hazard Scores
2023 Gary Hettinger University of Pennsylvania Estimation of Policy-relevant Causal Effects in the Presence of Interference with an Application to the Philadelphia Beverage Tax
2023 Jing Wang University of Connecticut Scale-invariant Optimal Sampling and Variable Selection with Rare-events Data
2023 Kaidi Kang Vanderbilt University Double Anchoring Events Based Sigmoidal Mixed Model: An Application in Alzheimer’s Disease Progression
2023 Penghui Huang University of Pittsburgh Accurate Estimation of Rare Cell Type Fractions from Tissue Omics Data via Hierarchical Deconvolution
2023 Tianle Liu Harvard University Wasserstein-p Bounds in the Central Limit Theorem under Weak Dependence
2023 Ye Tian Columbia University Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness