School of Engineering
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Edward Y. Chang
Affiliate, Computer Science
BioEdward Y. Chang has been an adjunct professor in Stanford’s Computer Science Department since 2019. Previously, he was a tenured professor at UC Santa Barbara. From 2006 to 2012, he served as a director at Google Research, where he pioneered data-centric and parallel machine learning and contributed to the ImageNet project. Chang later became president of HTC Healthcare, where he developed AI-powered diagnostics and won the Tricorder XPRIZE. He has also held positions at HKUST and UC Berkeley. Chang earned an MS in Computer Science and a PhD in Electrical Engineering from Stanford. He is a Fellow of ACM and IEEE for his contributions to scalable machine learning and healthcare AI.
Since 2019, Chang’s research has focused on virtual assistance, collaborating with Monica Lam, and more recently on large language models (LLMs). He hypothesizes that LLM Collaborative Intelligence (LCI) could pave the way toward artificial general intelligence (AGI).
Chang has authored seven books, including:
Unlocking the Wisdom of Large Language Models (2024)
LLM Collaborative Intelligence: The Path to Artificial General Intelligence (2024)
Journey of the Mind (Poetry, 2023)
Mandarin translation of Erwin Schrödinger’s What is Life? Mind and Matter (2021)
Big Data Analytics for Large-Scale Multimedia Search (2019)
Nomadic Eternity (Poetry, 2012)
Foundations of Large-Scale Multimedia Information Management and Retrieval (2011) -
Fu-Kuo Chang
Professor of Aeronautics and Astronautics
BioProfessor Chang's primary research interest is in the areas of multi-functional materials and intelligent structures with particular emphases on structural health monitoring, intelligent self-sensing diagnostics, and multifunctional energy storage composites for transportation vehicles as well as safety-critical assets and medical devices. His specialties include embedded sensors and stretchable sensor networks with built-in self-diagnostics, integrated diagnostics and prognostics, damage tolerance and failure analysis for composite materials, and advanced multi-physics computational methods for multi-functional structures. Most of his work involves system integration and multi-disciplinary engineering in structural mechanics, electrical engineering, signal processing, and multi-scale fabrication of materials. His recent research topics include: Multifunctional energy storage composites, Integrated health management for aircraft structures, bio-inspired intelligent sensory materials for fly-by-feel autonomous vehicles, active sensing diagnostics for composite structures, self-diagnostics for high-temperature materials, etc.
