The Student Poster Awards
The annual Student Poster Award is sponsored by the ASA Section on Statistics in Defense and National Security and recognizes the top student posters at DATAWorks. Posters are scored by a judging panel based on the impact and novelty of results, rigor of the analysis, clarity of presentation, and relevancy to the workshop. Undergraduate and graduate students from both civilian universities and military academies are eligible. Winners are awarded a certificate and cash prize.
2025 SPA
Ellis McLarty
Clemson University and Savannah River National Laboratory
Bayesian Statistical Analysis for Mass Spectrometric Data Processing
Federico Veneri
Iowa State University
Synthetic anchoring under the specific source problem
Anna Flowers
Virginia Tech
Computer Experiments for Meta-learning of Machine Learning Models
Sheyla Street
United States Military Academy
Creating a Robust Cyber Workforce
Alexander Boarnet
United States Military Academy
Confidence Based Skip-Lot Sampling
2024 SPA
Karen Alves da Mata
University of Massachusetts Dartmouth
Quantitative Reliability and Resilience Assessment of a Machine Learning Algorithm
Andrew Simpson
South Dakota State University
Clustering Singular and Non-Singular Covariance Matrices for Classification
Jason Ingersoll
United States Military Academy
Tactical Route Optimization: A Data Driven Method for Military Route Planning
Max Felter
United States Military Academy
Synthetic Data for Target Acquisition
2023 SPA
Madison McGovern
United States Military Academy
Data Fusion: Facilitating the Combination of Multiple Streams of Intelligence
Sumit Kumar Kar
University of North Carolina at Chapel Hill
A Generalized Influence Maximization Problem
Zheming Gou
University of Southern California
A Data-Driven Approach of Uncertainty Quantification on Reynolds Stress Based on DNS Turbulence Data
Zakaria Faddi
University of Massachusetts Dartmouth
Application of Software Reliability and Resilience Models to Machine Learning
Ebenezer Yawlui
University of Massachusetts Dartmouth
Optimal Release Policy for Covariate Software Reliability Models
2022 SPA
Takayuki Iguchi
Florida State University
Profile Monitoring via Eigenvector Perturbation
Anna Vinnedge
United States Military Academy
Utilizing Machine Learning Models to Predict Success in Special Operations Assessment
Brittany Fischer
Arizona State University
Optimal Designs for Multiple Response Distributions