Alexandre Adam

In this engaging conversation, Alexandre Adam, a PhD student in physics at the University of Montreal, dives into his compelling research on diffusion models. He sheds light on the challenges of navigating high-dimensional spaces in machine learning and optimizing neural networks using automatic differentiation. The dialogue explores data augmentation techniques for image analysis and examines how diffusion models aid in understanding galaxy images and their gravitational interactions. Alex's insights bridge complex mathematical concepts with real-world applications in astrophysics.