School of Engineering
Showing 201-220 of 496 Results
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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.
