Congratulations! relAI student Sameer Ambekar wins the best paper award at the MICCAI Workshop on Advancing Data Solutions in Medical Imaging AI (ADSMI).
Sameer is a PhD student at relAI, advised by the relAI Fellow Julia A. Schnabel. His research focusses on test-time adaptation and domain generalization for medical imaging.
His award-winning paper “Selective Test-Time Adaptation for Unsupervised Anomaly Detection using Neural Implicit Representations”, co-authored with Julia A. Schnabel and Cosmin Bereca, presents a novel zero-shot methodology to adapt models in real time to test images from new domains using deep pre-trained features. The approach is validated on brain anomaly detection data.
This work addresses domain shift at test-time, which Sameer explains in more detail in his recently published relAI blog post. In the post, you can also learn about the importance of handling domain shifts to make AI more reliable: https://zuseschoolrelai.de/blog/mitigating-domain-shifts/
Congratulations on this achievement!
