School of Engineering
Showing 101-200 of 200 Results
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Chunmei Zhao
Chief Education Solutions Officer, Stanford Engineering Center for Global and Online Education
Current Role at StanfordChief Education Solutions Officer, Stanford Center for Global & Online Education, School of Engineering.
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Renee Zhao
Assistant Professor of Mechanical Engineering and, by courtesy, of Materials Science and Engineering
BioRuike Renee Zhao is an Assistant Professor of Mechanical Engineering at Stanford University, where she directs the Soft Intelligent Materials Laboratory. Originally from the historic city of Xi'an, she earned her BS from Xi'an Jiaotong University in 2012. She then pursued Solid Mechanics at Brown University, obtaining her MS in 2014 and PhD in 2016. Following her doctoral studies, she completed postdoctoral training at MIT (2016–2018) before serving as an Assistant Professor at The Ohio State University (2018–2021).
Renee’s research focuses on developing stimuli-responsive soft composites for multifunctional robotic systems with integrated shape-changing, assembly, sensing, and navigation capabilities. By integrating mechanics, material science, and advanced material manufacturing, her work enables innovations in soft robotics, miniaturized biomedical devices, robotic surgery, origami systems, active metamaterials, and general deployable morphing structures.
Her contributions have been recognized with honors and awards, including the ARO Early Career Program (ECP) Award (2023), AFOSR Young Investigator Research Program (YIP) Award (2023), Eshelby Mechanics Award for Young Faculty (2022), ASME Henry Hess Early Career Publication Award (2022), ASME Pi Tau Sigma Gold Medal (2022), ASME Applied Mechanics Division Journal of Applied Mechanics Award (2021), NSF CAREER Award (2020), and ASME Applied Mechanics Division Haythornthwaite Research Initiation Award (2018). She is also recognized as a National Academy of Sciences Kavli Fellow and was named one of MIT Technology Review's 35 Innovators Under 35. -
Xiaolin Zheng
Professor of Mechanical Engineering, of Energy Science Engineering, Senior Fellow at the Precourt Institute for Energy and Professor, by courtesy, of Materials Science and Engineering
BioProfessor Zheng received her Ph.D. in Mechanical & Aerospace Engineering from Princeton University (2006), B.S. in Thermal Engineering from Tsinghua University (2000). Prior to joining Stanford in 2007, Professor Zheng did her postdoctoral work in the Department of Chemistry and Chemical Biology at Harvard University. Professor Zheng is a member of MRS, ACS and combustion institute. Professor Zheng received the TR35 Award from the MIT Technology Review (2013), one of the 100 Leading Global Thinkers by the Foreign Policy Magazine (2013), 3M Nontenured Faculty Grant Award (2013), the Presidential Early Career Award (PECASE) from the white house (2009), Young Investigator Awards from the ONR (2008), DARPA (2008), Terman Fellowship from Stanford (2007), and Bernard Lewis Fellowship from the Combustion Institute (2004).
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Zhuo Zheng
Postdoctoral Scholar, Computer Science
BioMy research interests are Earth Vision and AI4Earth, especially multi-modal and multi-temporal remote sensing image analysis and their real-world applications.
First-author representative works:
- Our Change family: ChangeStar (single-temporal learning, ICCV 2021), ChangeMask (many-to-many architecture, ISPRS P&RS 2022), ChangeOS (one-to-many architecture, RSE 2021), Changen (generative change modeling, ICCV 2023)
- Geospatial object segmentation: FarSeg (CVPR 2020) and FarSeg++ (TPAMI 2023), LoveDA dataset (NeurIPS Datasets and Benchmark 2021)
- Missing-modality all weather mapping: Deep Multisensory Learning (first work on this topic, ISPRS P&RS 2021)
- Hyperspectral image classification: FPGA (first fully end-to-end patch-free method for HSI, TGRS 2020) -
Henry Zhu
Ph.D. Student in Computer Science, admitted Autumn 2020
BioHenry Zhu is a PhD student in the Stanford AI Lab (SAIL).
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Mark Znidar
Undergraduate, Computer Science
BioUndergraduate studying mathematics and computer science, with research interests in relational learning, large-scale recommender systems, and predictive modelling. Previous experience includes algorithmic data science at Teads/Outbrain, data engineering at Robinhood, and multiple research internships. Interesting fact: I played professional basketball.
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Orr Zohar
Ph.D. Student in Electrical Engineering, admitted Autumn 2021
Masters Student in Computer Science, admitted Autumn 2023BioOrr Zohar, from Haifa, Israel, is pursuing a PhD in electrical engineering at Stanford School of Engineering. He graduated summa cum laude from the Technion with a bachelor's degree in chemical engineering and a master’s degree in electrical engineering. Orr aspires to research, develop, and translate novel machine learning methods into the open surgical domain for applications such as AI-assisted surgery and surgical skill evaluation. Currently, developing novel learning methods in open-world learning and action quality evaluation at MARVL, advised by Prof. Serena Yeung.
Before coming to Stanford, he was a machine learning and algorithms engineer at proteanTecs and a junior researcher at the Technion's LNBD, where he developed soft electronic platforms that can heal, detect damage, and serve as multifunctional electronic skins. During his undergraduate degree, Orr worked as a visiting undergraduate researcher at the de la Zerda group, Stanford University, where he developed OCT image processing algorithms for improved molecular contrast and depth-of-field. Orr is a Bazan Group scholar and was awarded the Sieden family prize for his contributions to YBCO-based photon detectors' development. -
James Zou
Associate Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering
Current Research and Scholarly InterestsMy group works on both foundations of statistical machine learning and applications in biomedicine and healthcare. We develop new technologies that make ML more accountable to humans, more reliable/robust and reveals core scientific insights.
We want our ML to be impactful and beneficial, and as such, we are deeply motivated by transformative applications in biotech and health. We collaborate with and advise many academic and industry groups. -
Adam Zsarnoczay
Senior Research Engineer
Current Research and Scholarly InterestsAdam's research focuses on disaster simulations that support multi-hazard risk assessment and management at a regional scale. His research interests include probabilistic natural hazard assessment, model development and calibration for structural response estimation and performance assessment, surrogate modeling and uncertainty quantification in large-scale, regional simulations, and using quantitative disaster simulations to support risk management and mitigation.
