Assistant Professor
Department of Statistics
Indiana University
919 E. 10th Street
Bloomington, IN 47408

Email: afmejia@iu.edu
Github: https://github.com/mandymejia
Twitter: @mandymejia

News

October 2019: Our new paper on fast, reliable estimation of subject-level brain networks using a hierarchical Bayesian framework with empirical “big data” population priors is now in press in Journal of the American Statistical Association! “Template Independent Component Analysis: Targeted and Reliable Estimation of Subject-level Brain Networks using Big Data Population Priors

September 2019: New paper in Nature Communications with Jorge Mejia and Franco Pestilli! “Open data on industry payments to healthcare providers reveals potential hidden costs to the public”

June 2019: New paper describing our method for estimating task activation on the cortical surface of the brain using spatial Bayesian modeling with INLA just published in Journal of the American Statistical Association! “A Bayesian General Linear Modeling Approach to Cortical Surface fMRI Data Analysis”

March 2019: Post-doc opportunity!  Details here.

January 2019: Mandy is awarded an NIH grant 1R01EB027119-01 on Bayesian methods for cortical surface neuroimaging data with co-investigators Martin Lindquist and Mary Beth Nebel.

December 24, 2018: Welcome to the world, Ana Lucia Mejia!

December 2018: Mandy is awarded a ASA Biometrics Section JSM 2019 travel award for the paper “A Bayesian General Linear Modeling Approach to Cortical Surface fMRI Data Analysis,” joint work with Ryan Yue, David Bolin, Finn Lindgren and Martin Lindquist.

May 2018: New manuscript, “Improved estimation of subject-level functional connectivity using full and partial correlation with empirical Bayes shrinkage” published in NeuroImage.