School of Engineering
Showing 101-200 of 446 Results
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Edward Y. Chang
Adjunct Lecturer, 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.
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Ray Chang
Postdoctoral Scholar, Bioengineering
Current Research and Scholarly Interestsfluid mechanics, ultrafast biophysics, protistology
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Ying Chih Chang
Adjunct Professor, Chemical Engineering
BioDr. Ying Chang is the Chair of the Taiwan Science and Technology Hub and an Adjunct Professor in the Department of Chemical Engineering at Stanford University. She is also the Founder and CEO of Acrocyte Therapeutics, Inc.
Her former faculty appointments include Research Fellow (-Associate Fellow) at the Genomics Research Center, Academia Sinica, Taiwan, and Assistant Professor in the Departments of Chemical Engineering and Materials Science, and Biomedical Engineering at the University of California, Irvine. The research highlights include integrating nanomaterials, microfluidics, and bioreactors to control cell fates for tissue engineering, as well as developing circulating tumor cell 3D culture for cancer diagnostics and precision medicine. She holds multiple patents in DNA microarray constructs (assigned to Affymetrix), circulating tumor cell isolation and cancer screening (assigned to Cellmax Life Inc.), and single cell derived scaffold free 3D culture platform RCE and circulating tumor cell liquid biopsy drug test (assigned to Acrocyte Therapeutics Inc. www.acrocyte.com).
Dr. Chang’s work was recognized by the Young Investigator Award from the Whitaker Foundation, FDA breakthrough device designation for pre-cancer and cancer detection (2021), Future Tech Award (2021), 18th National Innovation Award, Taiwan (2021), and Finalist at Startup Stadium at BIO 2024, among other. She is also on the board of trustees of Kaohsiaung Medical University, and Chang Chau-Ting Memorial Foundation, a non-profit organization for science education and awareness in Taiwan. She received her BS from National Taiwan University, and PhD from Stanford University, both in Chemical Engineering. -
Moses Charikar
Donald E. Knuth Professor
Current Research and Scholarly InterestsEfficient algorithmic techniques for processing, searching and indexing massive high-dimensional data sets; efficient algorithms for computational problems in high-dimensional statistics and optimization problems in machine learning; approximation algorithms for discrete optimization problems with provable guarantees; convex optimization approaches for non-convex combinatorial optimization problems; low-distortion embeddings of finite metric spaces.
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Ovijit Chaudhuri
Professor of Mechanical Engineering and, by courtesy, of Bioengineering
Current Research and Scholarly InterestsWe study the physics of cell migration, division, and morphogenesis in 3D, as well cell-matrix mechanotransduction, or the process by which cells sense and respond to mechanical properties of the extracellular matrices. For both these areas, we use engineered biomaterials for 3D culture as artificial extracellular matrices.
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Enze Chen
Lecturer
BioEnze (he/him, '18) is a Lecturer in Materials Science and Engineering (MSE) who teaches a variety of undergraduate MSE courses spanning structure, characterization, energy, computing, and communication. Midway through undergrad, he was introduced to the world of computational materials science and hasn't looked back, completing a PhD in MSE that applied computational tools to study planar defects and materials informatics education. Enze is excited to be back on The Farm and to help advance student success through instruction, advising, and research.
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Haoxuan Chen
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2022
BioPersonal website: https://haoxuanstevec00.github.io/
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Helen L. Chen
Research Scientist
BioHelen L. Chen is a research scientist in the Designing Education Lab in the Department of Mechanical Engineering at Stanford University. She holds an undergraduate degree in communication from UCLA and a PhD in communication with a minor in psychology from Stanford. Helen is a board member for the Association for Authentic, Experiential and Evidence-Based Learning (AAEEBL) and is a co-author of Documenting Learning with ePortfolios: A Guide for College Instructors and co-executive editor of the International Journal of ePortfolio. She works closely with the Association of American Colleges and Universities and consults with institutions on general education redesign, authentic assessment approaches, design thinking, and personal branding and ePortfolios. Helen's current research and scholarship focus on engineering and entrepreneurship education; the pedagogy of portfolios and reflective practice in higher education; and redesigning how learning is recorded and recognized in traditional transcripts and academic credentials.
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Hugo Chen
Ph.D. Student in Electrical Engineering, admitted Autumn 2022
BioHugo "Jiun-Yu" Chen is currently pursuing his Ph.D. degree in the Department of Electrical Engineering at Stanford University. He earned his M.S. in Photonics and Optoelectronics from National Taiwan University in 2019 and his B.S. in Materials Science and Engineering from National Dong Hwa University in 2017.
Prior to joining Stanford, Hugo worked as an R&D engineer at Taiwan Semiconductor Manufacturing Company (TSMC) in the High Power Program and Analog Power/RF Specialty Technology from 2019 to 2022. His research experience includes investigating GaN high electron mobility transistors (HEMTs) for high power converter applications, oxide-based thin-film transistors (TFTs) for CMOS inverter applications, and III-V quantum dots molecular beam epitaxy (MBE) material growth.
As the first author, Hugo has published two peer-reviewed journal articles, six conference papers, and one US/KR/TW/CN/DE patent. He is currently advised by Professors H.-S. Philip Wong and Kwabena Boahen, and his research focuses on developing ferroelectric field-effect transistors (FeFETs) for dendritic-centric learning.
In his leisure time, Hugo enjoys biking, playing badminton, and watching dramas. -
Jianqing Chen
Affiliate, Mechanical Engineering - Design
Visiting Scholar, Mechanical Engineering - DesignBioMy work focuses on robotic remote control and manipulation systems utilizing reinforcement learning (RL). The research centers on developing RL-based algorithms that enable robots to learn optimal control strategies for tasks such as navigation, object manipulation, and interaction within dynamic environments. By training robots through iterative trial-and-error processes, these systems continuously improve performance, adapt to new situations, and enhance autonomous control. The broader goal is to achieve more efficient, precise, and scalable robotic behavior in real-world applications.
In parallel, I have over seven years of experience in investment and asset management. I lead 280 Capital, a family-backed investment office overseeing more than $1 billion across digital assets and emerging technologies.
My technical background spans artificial intelligence, enterprise storage systems, encryption, and large-scale computing infrastructure. I contributed to the design of next-generation enterprise SSD controller and storage system chips ranging from 16nm to 7nm at Broadcom and SK Hynix. At Roche, I led the construction and optimization of large-scale biodata software and hardware architectures supporting advanced DNA sequencing and scalable computational biology workloads. I also hold multiple U.S. patents related to improving storage and computing efficiency through deep learning, AI, and advanced systems design. -
Jieneng Chen
Affiliate, Program-Wu, J.
BioJieneng Chen is a postdoctoral researcher at Stanford SVL, working with Prof. Jiajun Wu. He received the PhD in Computer Science at Johns Hopkins University in 2026. He is a recipient of Siebel Scholar award, Nvidia academic grant, multiple best paper awards, young american scientist award, and young investigator awards.
