School of Engineering
Showing 6,901-7,000 of 7,031 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 and, 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) -
(Andrew) Zhanke Zhou
Graduate, Computer Science
BioI am a visiting student working with Prof. Sanmi Koyejo. My research focuses on trustworthy machine reasoning with foundation models to solve complex problems such as mathematics, coding, and planning, as well as to accelerate scientific discovery and application in fields like biology, chemistry, and healthcare.
I believe that reasoning is the essential pathway to achieving AGI. Trustworthy machine reasoning encompasses properties such as reasoning power, robustness, safety, and explainability. My work involves developing methodologies, benchmarks, and theoretical foundations to advance these areas.
I am always open for possible collaborations. Please feel free to email me for research, collaborations, or a casual chat.
Personal website: https://andrewzhou924.github.io/
Email: andrewzhou924@gmail.com -
Henry Zhu
Ph.D. Student in Computer Science, admitted Autumn 2020
BioHenry Zhu is a PhD student in the Stanford AI Lab (SAIL).
