Bio · Yang is a Senior Staff Research Scientist at Google DeepMind, and an affiliate faculty member at University of Washington CSE. He earned a Ph.D. degree in Computer Science from the Chinese Academy of Sciences, and conducted postdoctoral research at UC Berkeley EECS. Yang significantly contributed to UI Understanding and Generation by extensively developing deep learning methods and benchmarks to tackle the unique challenges in the area, and helping popularize deep learning as a common approach for computational UI understanding. He pioneered on-device interactive ML on Android by developing impactful product features such as next app prediction and Gesture Search. Yang has extensively published in top venues across both the HCI and ML fields, including CHI, UIST, ICML, ACL, EMNLP, CVPR, NeurIPS (NIPS), ICLR and KDD, and has constantly served as area chairs or senior area (track) chairs across the HCI and ML fields. Yang is an editor of the Springer book on AI for HCI: A Modern Approach, and an organizer of multiple workshops that bridges the HCI and AI/ML field, including the first AI&HCI workshp at ICML.