Zihang Wang, Irina Gaynanova, Aleksandr Aravkin, and Benjamin B. Risk recently won the JASA Reproducibility Award for “Sparse Independent Component Analysis with an Application to Cortical Surface fMRI Data in Autism.”
Additionally, Wentao Zhan and Abhirup Datta won the award for “Neural Networks for Geospatial Data.”
The Journal of the American Statistical Association Reproducibility Award, established in 2023 by the JASA editorial board and implemented by the JASA associate editors of reproducibility, aims to recognize outstanding papers from JASA Applications and Case Studies or JASA Theory and Methods in terms of their computational reproducibility.
The award will be presented to the authors during the Joint Statistical Meetings in Nashville, Tennessee. Visit the award website for an overview of the award process and criteria.
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