Difference between revisions of "SOCR News AmStats SIM 2024"

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(Created page with "== SOCR News & Events: 2024 2024 American Statistical Association Special Session on Longitudinal Imaging and Biostatistical Methods, Statistics in Imaging Ann...")
 
(Session Presenters)
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==Session Presenters==
 
==Session Presenters==
* Sharmistha Guha (TAMU)
+
* [https://sites.google.com/view/sharmisthaguha Sharmistha Guha] (TAMU)
 
: ''Title'': Bayesian approaches for Modeling Brain Network Dynamics.
 
: ''Title'': Bayesian approaches for Modeling Brain Network Dynamics.
  
* Hossein Moradi (SDState)
+
* [https://www.sdstate.edu/directory/hossein-moradi Hossein Moradi] (SDState)
 
: ''Title'': Spatiotemporal dimension reduction and biomedical imaging data analytics
 
: ''Title'': Spatiotemporal dimension reduction and biomedical imaging data analytics
  
* Ranjan Maitra (Iowa)
+
* [https://www.stat.iastate.edu/people/ranjan-maitraRanjan Maitra] (Iowa State)
 
: ''Title'': Complex-valued time series modeling and prediction in high-dimensional spatiotemporal processes
 
: ''Title'': Complex-valued time series modeling and prediction in high-dimensional spatiotemporal processes
  
* Dan Rowe (Marquette)
+
* [https://www.marquette.edu/mathematical-and-statistical-sciences/directory/daniel-rowe.php Dan Rowe] (Marquette)
 
: ''Title'': (TBD)
 
: ''Title'': (TBD)
 
   
 
   
* Ivo Dinov (Michigan)
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* [https://www.socr.umich.edu/people/dinov/ Ivo Dinov] (Michigan)
 
: ''Title'': Spacekime analytics: from time-series to kime-surfaces and inference-functions
 
: ''Title'': Spacekime analytics: from time-series to kime-surfaces and inference-functions
  

Revision as of 13:46, 15 February 2024

SOCR News & Events: 2024 2024 American Statistical Association Special Session on Longitudinal Imaging and Biostatistical Methods, Statistics in Imaging Annual Meeting, Indianapolis

Overview

This session will include a blend of mathematical, statistical, and computational experts presenting on recent methodological advances to represent, model, predict, synthesize, and analyze large and heterogeneous spatiotemporal imaging data.


Session Logistics

Session Presenters

Title: Bayesian approaches for Modeling Brain Network Dynamics.
Title: Spatiotemporal dimension reduction and biomedical imaging data analytics
Title: Complex-valued time series modeling and prediction in high-dimensional spatiotemporal processes
Title: (TBD)
Title: Spacekime analytics: from time-series to kime-surfaces and inference-functions





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