Pascal Fua from EPFL presented an approach to implementing convolutional neural nets that output complex 3D surface meshes. The method overcomes limitations in converting implicit representations to explicit surface representations. Applications include single view reconstruction, physically-driven shape optimization, and bio-medical image segmentation. Why it matters: This research advances geometric deep learning by enabling end-to-end trainable models for 3D surface mesh generation, with potential impact on various applications in computer vision and biomedical imaging in the region.
Dr. Mohammad Yaqub, an Assistant Professor at MBZUAI, leads the BioMedIA lab and focuses on applying AI to real-world healthcare challenges, particularly in smart imaging. He was inspired by a textbook by Tom Mitchell and his work at Oxford University where he helped develop ScanNav, an AI solution aiding sonographers in anomaly scans during pregnancy. ScanNav assists in assessing fetal growth and detecting abnormalities, potentially improving early intervention. Why it matters: This highlights the growing importance of AI in enhancing medical diagnostics and improving healthcare outcomes in the UAE and globally.