School of Engineering
Showing 1-50 of 277 Results
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Simone D'Amico
Associate Professor of Aeronautics and Astronautics and, by courtesy, of Geophysics
BioSimone D’Amico is Associate Professor of Aeronautics and Astronautics (AA), W.M. Keck Faculty Scholar in the School of Engineering, and Professor of Geophysics (by Courtesy). He is the Founding Director of the Space Rendezvous Laboratory and Director of the AA Undergraduate Program. He received the B.S. and M.S. degrees from Politecnico di Milano (2003) and the Ph.D. degree from Delft University of Technology (2010). Before Stanford, Dr. D’Amico was research scientist and team leader at the German Aerospace Center (DLR) for 11 years. There he gave key contributions to formation-flying and proximity operations missions such as GRACE (NASA/DLR), PRISMA (OHB/DLR/CNES/DTU), TanDEM-X (DLR), BIROS (DLR) and PROBA-3 (ESA). His research aims at enabling future miniature distributed space systems for unprecedented remote sensing, space and planetary science, exploration and spaceflight sustainability. To this end he performs fundamental and applied research at the intersection of advanced astrodynamics, spacecraft Guidance, Navigation and Control (GNC), autonomy, decision making and space system engineering. Dr. D’Amico is institutional PI of three upcoming autonomous satellite swarm missions funded by NASA and NSF, namely STARLING, VISORS, and SWARM-EX. He is Fellow of AAS, Associate Fellow of AIAA, Associate Editor of AIAA JGCD, Advisor of NASA and several space startups. He was the recipient of several awards, including Best Paper Awards at IAF (2022), IEEE (2021), AIAA (2021), AAS (2019) conferences, the Leonardo 500 Award by the Leonardo da Vinci Society/ISSNAF (2019), FAI/NAA’s Group Diploma of Honor (2018), DLR’s Sabbatical/Forschungssemester (2012) and Wissenschaft Preis (2006), and NASA’s Group Achievement Award for the GRACE mission (2004).
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Marta D'Elia
Adjunct Professor, Institute for Computational and Mathematical Engineering (ICME)
BioI’m a research/computational scientist working on the design and analysis of models and data-driven algorithms for the simulation of complex, multiscale and multiphysics problems. My background and training have foundations in Numerical Analysis, Scientific Computing, Inverse Problems, Control and Optimization, and Uncertainty Quantification. In the past five years I have focused on Scientific Machine Learning (SciML) and Deep Learning. I am an expert in Nonlocal/Fractional Modeling and Simulation (10 years) with application to Continuum Mechanics, Subsurface Transport, Image Processing, and Turbulence. I have a master's degree in Mathematical Engineering from Politecnico di Milano (2007) and a PhD in Applied Mathematics from Emory University (2011).
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David Dai
Masters Student in Computer Science, admitted Autumn 2022
BioI am a masters student at Stanford University majoring in Computer Science. I am currently in Stanford SVL and Partnership in AI-Assisted Care (PAC) Lab supervised by Dr. Fei-Fei Li and Dr. Ehsan Adeli.
Before joining Stanford, I graduated with the highest honor in Computer Science and Math from Emory University. I was in the Emory Brain Network Lab under the supervision of Dr. Carl Yang working on graph mining in the area of healthcare.
My research interests lie in computer vision, graph learning, bioinformatics, AI in healthcare, interpretation, and explainability. -
Onat Dalmaz
Ph.D. Student in Electrical Engineering, admitted Autumn 2023
Current Research and Scholarly InterestsI am interested in developing novel deep generative models for multi-modal medical imaging, particularly for medical image synthesis. My research aims to improve diagnostic information and patient comfort while decreasing examination costs and toxicity/radiation exposure. I devise new deep architectures and robust learning strategies for medical image reconstruction and synthesis techniques.
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Margaret Daly
Ph.D. Student in Civil and Environmental Engineering, admitted Spring 2018
Grader, Civil and Environmental EngineeringBioMargaret Daly is a Ph.D. Candidate studying Environmental Fluid Mechanics in CEE. She is interested in using novel approaches for coastal oceanography and interdisciplinary work towards ocean sustainability. She researches ocean flow through kelp forests, and the impact on benthic species, particularly abalone in Baja California, Mexico. She also studies how kelp plants move in different currents and wave conditions to better parameterize drag for coastal ocean models. In addition to her research in fluid mechanics, Daly is also interested in ocean policy and illegal fishing mitigation strategies. With the Stanford Center for Ocean Solutions, Daly is developing a risk tool for global seafood supply chains to use in assessing current vulnerability to illegally caught seafood. Lastly, Margaret is combining ocean drone imagery with machine learning detect sea otters on the California Coast. Margaret is an experienced scientific diver with over 200 dives and 5 field campaigns. In the future, Daly is interested in working on problem in other coastal ecosystems such as coral reef or sea grass habitats, working with small scale fishery communities, and on policy to support ocean sustainability.
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Bruce Daniel
Professor of Radiology (Body Imaging) and, by courtesy, of Bioengineering
On Partial Leave from 11/22/2023 To 12/22/2023Current Research and Scholarly Interests1. MRI of Breast Cancer, particularly new techniques. Currently being explored are techniques including ultra high spatial resolution MRI and contrast-agent-free detection of breast tumors.
2. MRI-guided interventions, especially MRI-compatible remote manipulation and haptics
3. Medical Mixed Reality. Currently being explored are methods of fusing patients and their images to potentially improve breast conserving surgery, and other conditions. -
Eric Darve
Professor of Mechanical Engineering
Current Research and Scholarly InterestsThe research interests of Professor Darve span across several domains, including machine learning for engineering, surrogate and reduced order modeling, stochastic inversion, anomaly detection for engineering processes and manufacturing, numerical linear algebra, high-performance and parallel computing, and GPGPU.
