The 2023 Statistical Methods in Imaging Conference took place this week in Minneapolis. Investigators and students from around the country gathered to discuss and share their work in the field of imaging science. We are proud of our department members who presented at the conference. They include the following:
Monday, May 22
PhD student Jiangmei “Ruby” Xiong presented a poster for “Application of Closed-Form Gamma Mixture Model in mxIF Cell Gating.” Assistant professor Simon Vandekar co-authored the poster.
Tuesday, May 23
Simon Vandekar was an organizer for the invited session “New Statistical Methods to Improve the Spatial-Omics Analysis Pipeline.”
Simon was also a session organizer for “Collaborative Case Study: Statistical Methods and Findings from Large Consortia Studies.” PhD student Kaidi Kang was an invited speaker in the session and presented “Study Features Impacting Replicability of Brain-wide Association Studies.”
Assistant professor Panpan Zhang was an invited speaker in the session “Recent Advances in Neuroimaging Statistics for Investigating Human Brain Function.” He presented “A Bayesian Model for Link Prediction in Functional Brain Networks.”
Wednesday, May 24
Ruby Xiong was a session organizer for “Recent Advances in Spatial Analysis of Single-Cell Imaging.” Assistant professor Siyuan Ma was an invited speaker during this session and presented “A Flexible Generalized Linear Mixed Effects Model for Testing Cell-Cell Colocalization in Spatial Immunofluorescent Data.”
Congratulations to everyone!