Announcement_eurips

Presented two posters at the AI conference EurIPS in Copenhagen! 🔥

I attended the european counterpart of the top-tier ML conference NeurIPS in Copenhagen, where I presented my Bayesian mixture modeling framework to evaluate the reliability of repeated measurements in brain networks. The model represents each connection as a probabilistic mixture capturing the presence or absence of a true brain connection and estimates reliability across repeated measurements. We first validated the approach using synthetic repeated-measures data with controlled noise mimicking real neuroimaging variability, before applying it to real datasets. The model successfully detected connections with varying reliability and produced biologically meaningful estimates, while also revealing important limitations in recovering absent connections. Although developed for brain connectivity, the framework is broadly applicable to any network derived from repeated observations where uncertainty quantification is critical. The conference was additionally a great opportunity to learn more about the latest advances in deep learning research, reconnect with friends and former colleagues, and exchange ideas with the community. Exploring the beautiful harbor of Copenhagen was also a wonderful highlight of the trip.