AI Inroads in Imaging Sciences for Materials Research - IPAM at UCLA

Explore the impact of deep learning on materials research in this 48-minute lecture from the Mathematical Advances for Multi-Dimensional Microscopy Workshop at IPAM. Delve into how artificial intelligence is revolutionizing imaging sciences, with a focus on deep convolutional neural networks and their applications in transmission electron microscopy and tomographic imaging. Gain insights into the potential of AI to accelerate the discovery of new theories and materials, drawing parallels from its success in cognitive game theory, pattern recognition, and bioinformatics. Presented by Huolin Xin from the University of California, Irvine, this talk offers a comprehensive look at the intersection of AI and materials science, demonstrating the transformative power of machine learning in scientific research.