School of Engineering
Showing 901-1,000 of 6,593 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 - DesignBioI work on robotic remote control and manipulation systems utilizing reinforcement learning (RL). My focus is on developing RL-based algorithms that enable robots to learn optimal control strategies for tasks such as navigation, object manipulation, and interaction with dynamic environments. By training robots through trial and error, these systems continuously improve their performance, adapting to new situations and enhancing autonomous control. The goal is to achieve more efficient and precise robot behavior in real-world applications.
I worked over 7 years in investment and asset management. I lead 280 Capital, a Multi-Family Office with over $600M under management, focus on digital assets and cutting-edge technologies.
I have a strong background in AI, Storage, Encryption etc. I am in the great team to do designs in the latest enterprise-grade storage SSD system chips, from 16nm to 7nm, at Broadcom and SK Hynix. I also led the construction and optimization of large-scale biodata software and hardware data architectures at Roche to support scalable advanced DNA sequencing computations. I hold multiple U.S. patents, using various methods such as deep learning and AI to improve storage and computing efficiency. -
Po-Han Chen
Ph.D. Student in Electrical Engineering, admitted Winter 2021
BioPo-Han Chen is an EE Ph.D. student at Stanford University supervised by Prof. Priyanka Raina. He received his B.S. in Electrical Engineering and Computer Science (EECS) and M.S. in Electrical Engineering from National Tsing Hua University (Taiwan) in 2016 and 2018 respectively. Before joining Stanford, he was a digital circuit designer at MediaTek where he worked on developing hardware architectures of image processing pipeline. He is interested in designing hardware accelerators. Most of his previous works were related to computational photography algorithms such as digital refocusing. Currently, He is focusing on analyzing and designing architecture of CGRAs to create high-performance, energy-efficient, and reconfigurable computing platforms.
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Bo Wun Cheng
Ph.D. Student in Electrical Engineering, admitted Autumn 2023
BioBo-Wun Cheng is an EE Ph.D. student at Stanford University supervised by Prof. Priyanka Raina. He received his B.S. and M.S. degrees in Computer Science from National Tsing Hua University (Taiwan) in 2021 and 2023, respectively. His current research interest resides in designing and architecting efficient hardware accelerators. Before joining Stanford, his research spans the fields of Graphics Processing Unit memory architecture design and computer vision.
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Dali Cheng
Ph.D. Student in Electrical Engineering, admitted Autumn 2021
Current Research and Scholarly InterestsA light chaser studying photonics both theoretically and experimentally. I am devoted to understanding and improving our world using photonic science and engineering.
My current interest includes photonic systems with nontrivial topology, non-Hermiticity, non-Abelian gauge fields, and in the synthetic dimension. -
E.J. Chichilnisky
John R. Adler Professor, Professor of Neurosurgery and of Ophthalmology and, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsFunctional circuitry of the retina and design of retinal prostheses
