School of Engineering
Showing 6,801-6,900 of 7,042 Results
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Tony Zahtila
Postdoctoral Scholar, Mechanical Engineering
BioI am a Postdoctoral Fellow at the Center for Turbulence Research.
I received my PhD in Australia from the University of Melbourne in 2023.
My PhD research focused on the physics and computing strategies of multiphase flows. More recently, my interests are in multi-fidelity simulation ensembles and uncertainty quantification. -
Mohammad Asif Zaman
Postdoctoral Scholar, Electrical Engineering
Current Research and Scholarly InterestsMy research focuses on trapping and controlled manipulation of sub-micron sized particles. The work included modeling, fabrication and testing of chips that employ optical forces and/or dielectrophoretic forces to trap and transport nanoparticles. Our goal is to develop lab-on-a-chip systems for biomedical and chemical applications.
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Howard Zebker
Professor of Electrical Engineering and of Geophysics
Current Research and Scholarly InterestsResearch
My students and I study the surfaces of Earth and planets using radar remote sensing methods. Our specialization is interferometric radar, or InSAR. InSAR is a technique to measure mm-scale surface deformation at fine resolution over wide areas, and much of our work follows from applying this technique to the study of earthquakes, volcanoes, and human-induced subsidence. We also address global environmental problems by tracking the movement of ice in the polar regions. whose ice mass balance affects sea level rise and global climate. We participate in NASA space missions such as Cassini, in which we now are examining the largest moon of Saturn, Titan, to try and deduce its composition and evolution. Our work includes experimental observation and modeling the measurements to best understand processes affecting the Earth and solar system. We use data acquired by spaceborne satellites and by large, ground-based radar telescopes to support our research.
Teaching
I teach courses related to remote sensing methods and applications, and how these methods can be used to study the world around us. At the undergraduate level, these include introductory remote sensing uses of the full electromagnetic spectrum to characterize Earth and planetary surfaces and atmospheres, and methods of digital image processing. I also teach a freshman and sophomore seminar course on natural hazards. At the graduate level, the courses are more specialized, including the math and physics of two-dimensional imaging systems, plus detailed ourses on imaging radar systems for geophysical applications.
Professional Activities
InSAR Review Board, NASA Jet Propulsion Laboratory (2006-present); editorial board, IEEE Proceedings (2005-present); NRC Earth Science and Applications from Space Panel on Solid Earth Hazards, Resources, and Dynamics (2005-present); Chair, Western North America InSAR (WInSAR) Consortium (2004-06); organizing committee, NASA/NSF/USGS InSAR working group; International Union of Radioscience (URSI) Board of Experts for Medal Evaluations (2004-05); National Astronomy and Ionospheric Center, Arecibo Observatory, Visiting Committee, (2002-04; chair, 2003-04); NASA Alaska SAR Facility users working group (2000-present); associate editor, IEEE Transactions on Geoscience and Remote Sensing (1998-present); fellow, IEEE (1998) -
Ke Zeng
Postdoctoral Scholar, Electrical Engineering
BioKe Zeng received his Ph.D. and MS degree in the Electrical Engineering Department of SUNY-Buffalo. His current research is focused on fabricating various high power/performance electronic devices based on GaN and Ga2O3, especially utilizing various novel edge termination techniques and device structures, as well as understanding the fundamental physics underlying these devices.
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Xianfeng Zeng
Postdoctoral Scholar, Bioengineering
BioPh.D. in Chemistry, Princeton University (2023)
B.Sc. in Chemistry, Tsinghua University (2017) -
Hanfeng Zhai
Ph.D. Student in Mechanical Engineering, admitted Autumn 2023
BioWorking on combining multiscale and multiphysics computational modeling with scientific machine learning and design optimization for mechanical and materials design in various engineering fields in biomedicine, semiconductors, and manufacturing. Previous works include Bayesian optimization for antibiofilm surfaces, porous metamaterials, physics-informed learning for bubble dynamics, molecular dynamics of graphene, etc. Have industrial experience in multiscale modeling for semiconductor manufacturing at Tokyo Electron.
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Xianghao Zhan
Ph.D. Student in Bioengineering, admitted Autumn 2019
Ph.D. Minor, Biomedical Data Science
Student Employee, DASHBioXianghao Zhan is a 5th -year Ph.D. candidate at Stanford Bioengineering. He obtained his M.S in Bioengineering in 2021 and his M.S in Statistics in 2023 both at Stanford. Before that he got B. Eng. in Control Science and Engineering (Automation) and his B. Art in English Language and Literature with Summa Cum Laude at Chu Kochen Honors College, Zhejiang University, China, in 2019.
Under the guidance of Prof. Oliver Gevaert and Prof. David B. Camarillo, he mainly focuses on the optimization of computational modeling of traumatic brain injury with machine learning and animal modeling based on biomechanical and radiological data. His research interests and projects also extend to the data mining of free-text clinical notes with natural language processing, biomedical data fusion for COVID-19 patient outcome prediction, machine learning reliability quantification with conformal prediction, reliability-based semi-supervised learning, and domain adaptation for biomedical sensory systems (with artificial olfaction systems and surface electromyography systems). He has published 18 peer-reviewed articles as a first/co-first author (IF 131.3) in such journals as NPJ Digital Medicine, IEEE Transactions on Biomedical and Health Informatics, IEEE Transactions on Biomedical Engineering, Journal of Sport and Health Science, with 4 first-author journal articles under review. He has been a peer reviewer for 16 journals including Annals of Biomedical Engineering, Journal of Neurotrauma, Computer methods in biomechanics and biomedical engineering.
In addition to his research, he has two master degrees while pursuing his Ph.D. degree: BIOE 2021 and STATS 2023. He has taken more than 10 data science and machine learning courses at Stanford with course project experiences and technical background with UNet-based image segmentation, BERT, Transformer-XL, DeepSEA, BPNet, VAE/SSVAE, flow model, energy-based model cycle-GAN, CNN-based image classification, LSTM-based clinical event prediction, Bi-LSTM-based neural machine translation, BERT, DCT/DWT/STFT, PCA, DRCA, NFL, convex optimization.
His research is recognized by the field and he was awarded with IET Postgraduate Research Award for an Outstanding Researcher (one awardee across the globe, first Chinese), Siebel Scholar Class of 2024, IET Healthcare Technology William James Award (one awardee across the globe), Stanford Interdisciplinary Graduate Fellowship (highest honor for interdisciplinary Stanford graduates), Pfeiffer Research Foundation Fellow, AMIA Trainee Award (six awardees, the only Chinese), American Society of Neurotrauma Trainee Award (20 awardees, the only Chinese), Chu Kochen Scholarship (12/23,000), Ten most Preeminent Students of Zhejiang University (10/36,000), Chinese National Scholarship (Top 0.2%).
He is dedicated to support underrepresented minorities. He has been a program leader for Stanford Summer Research Program and mentored 3 undergrads from the underrepresented minorities. He has been a research mentor at Foothill College for two years and mentored latino students from local community college. Additionally, he is a sports fan with 13 Stanford Intramural champions (10 volleyball, 3 tennis) and two medals from regional volleyball tournaments. He enjoys the sport passion and team spirits as a captain. -
Anqi Zhang
Postdoctoral Scholar, Chemical Engineering
BioDr. Anqi Zhang is currently a postdoctoral scholar advised by Professor Zhenan Bao in the Department of Chemical Engineering and Professor Karl Deisseroth in the Department of Bioengineering at Stanford University. She received her Ph.D. degree under the supervision of Professor Charles M. Lieber in the Department of Chemistry and Chemical Biology at Harvard University in 2020, and her B.S. degree in Materials Chemistry from Fudan University in 2014. She is interested in combining novel electronic, chemical, and genetic tools to monitor and modulate neural circuits in a minimally invasive manner. Her research is funded by the American Heart Association (AHA) postdoctoral fellowship and the National Institutes of Health (NIH) K99/R00 award.
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Lifu Zhang
Graduate, Stanford Center for Professional Development
BioSoftware engineer at Google, AI researcher, Physics researcher
