Pablo Damasceno, PhD, is an Associate Director of Data Science at Johnson & Johnson, where he leads the video understanding team developing, validating, and deploying video-based AI to improve clinical trial measurement and disease characterization. His background spans applied machine learning, medical imaging, and computational physics, including prior work at UCSF’s Center for Intelligent Imaging advancing deep learning methods for neuroimaging and digital health. He focuses on building reliable, clinically grounded AI systems across endoscopy, ultrasound, and echocardiography - translating cutting-edge computer vision research into tools that strengthen evidence generation and accelerate drug development.