School of Engineering
Showing 161-180 of 689 Results
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John Eaton
Charles Lee Powell Foundation Professor in the School of Engineering, Emeritus
BioEaton uses experiments and computational simulations to study the flow and heat transfer in complex turbulent flows, especially those relevant to turbomachinery, particle-laden flows, and separated flows, and to develop new techniques for precise control of gas and surface temperature during manufacturing processes.
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Christopher Edwards
Professor of Mechanical Engineering, Emeritus
BioThe Edwards research group is focused on fundamental research for advanced energy technologies. The group performs theoretical and experimental studies of energy transformations such that the conversion process can be made cleaner, more efficient, and more controllable than has been possible with traditional technologies. Applications include advanced transportation engines (piston and turbine) and advanced electric power generation with carbon mitigation.
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Matthew R. Edwards
Assistant Professor of Mechanical Engineering
BioMatthew Edwards is an Assistant Professor of Mechanical Engineering. His research applies high-power lasers to the development of optical diagnostics for fluids and plasmas, the study of intense light-matter interactions, and the construction of compact light and particle sources, combining adaptive high-repetition-rate experiments and large-scale simulations to explore new regimes in fluid mechanics, thermodynamics, materials science, and plasma physics.
Matthew received BSE, MA, and PhD degrees in Mechanical and Aerospace Engineering from Princeton University. He was then a Lawrence Fellow in the National Ignition Facility and Photon Science Directorate at Lawrence Livermore National Laboratory. -
Charles (Chuck) Eesley
Professor of Management Science and Engineering
Current Research and Scholarly InterestsMy research focuses on the influence of the external environment on entrepreneurship. I investigate the types of environments that encourage the founding of high growth, technology-based firms. I build on previous literature that explains why entrepreneurs are successful and my major contribution is to demonstrate that institutions matter. I show that effective institutional change influences who starts firms, not just how many firms are started.
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Kathleen Eisenhardt
Stanford W. Ascherman, M.D. Professor in the School of Engineering, Emerita
Current Research and Scholarly InterestsTheoretical approaches: Cognition, complexity, learning, and organizational theories
Methods: Multi-case Theory Building as well as machine learning, simulation, and econometrics
Recent research: Business model design, strategy as "simple rules" heuristics, strategic interaction in novel markets and ecosystems, strategy in marketplaces, communities v. firm organizational forms -
Abbas El Gamal
Hitachi America Professor in the School of Engineering and Senior Fellow at the Precourt Institute for Energy
BioAbbas El Gamal is the Hitachi America Professor in the School of Engineering and Professor in the Department of Electrical Engineering at Stanford University. He received his B.Sc. Honors degree from Cairo University in 1972, and his M.S. in Statistics and Ph.D. in Electrical Engineering both from Stanford University in 1977 and 1978, respectively. From 1978 to 1980, he was an Assistant Professor of Electrical Engineering at USC. From 2003 to 2012, he was the Director of the Information Systems Laboratory at Stanford University. From 2012 to 2017 he was Chair of the Department of Electrical Engineering at Stanford University. His research contributions have been in network information theory, FPGAs, and digital imaging devices and systems. He has authored or coauthored over 230 papers and holds 35 patents in these areas. He is coauthor of the book Network Information Theory (Cambridge Press 2011). He has received several honors and awards for his research contributions, including the 2016 Richard W. Hamming Medal, the 2012 Claude E. Shannon Award, and the 2004 INFOCOM Paper Award. He is a member of the U.S. National Academy of Engineering and a Fellow of the IEEE. He has co-founded and served on the board of directors and advisory boards of several semiconductor and biotechnology startup companies.
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Sigrid Elschot
Professor of Aeronautics and Astronautics
BioSigrid Elschot is a Professor of Aeronautics and Astronautics and founding director of the Space Environment and Satellite Systems laboratory. Her research focuses on understanding and mitigating the space environment to enable more resilient spacecraft for interplanetary and interstellar exploration. Her work includes space weather detection and modeling, which is central to Space Situational Awareness (SSA) and Space Domain Awareness (SDA), achieved by integrating in situ and remote sensing data with high fidelity simulations to characterize space hazards. Current efforts include experimental and computational studies of hypervelocity dust and debris impacts on spacecraft using dust accelerators, light-gas guns, and Particle-In-Cell simulations, and ground-based radar to remotely characterize space debris and meteoroid populations. Prof. Elschot also leads research programs in hypersonic plasma physics relevant to atmospheric re-entry vehicles, and space energy harvesting for spacecraft power and propulsion. Prof. Elschot has been the recipient of several awards, including the Presidential Early Career Award for Scientists and Engineers (PECASE), NSF CAREER award, DoE CAREER award, Outstanding Mentor Award and Outstanding Professor in Aeronautics and Astronautics.
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Drew Endy
Associate Professor of Bioengineering and Senior Fellow, by courtesy, at the Hoover Institution and at the Freeman Spogli Institute for International Studies
Current Research and Scholarly InterestsWe work to strengthen the foundations and expand the frontiers of synthetic biology. Our foundational work includes (i) advancing reliable reuse of bio-measurements and -materials via standards that enable coordination of labor, and (ii) developing and integrating measurement and modeling tools for representing and analyzing living matter at whole-cell scales. Our work beyond the frontiers of current practice includes (iii) bootstrapping biotechnology tools in unconventional organisms (e.g., mealworms, wood fungus, skin microbes), and (iv) exploring the limits of whole-genome recoding and building cells from scratch. We also support strategy and policy work related to bio-safety, security, economy, equity, justice, and leadership.
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Barbara Elizabeth Engelhardt
Professor (Research) of Biomedical Data Science and, by courtesy, of Statistics and of Computer Science
BioBarbara E Engelhardt is a Senior Investigator at Gladstone Institutes and Professor at Stanford University in the Department of Biomedical Data Science. She received her B.S. (Symbolic Systems) and M.S. (Computer Science) from Stanford University and her PhD from UC Berkeley (EECS) advised my Prof. Michael I Jordan. She was a postdoctoral fellow with Prof. Matthew Stephens at the University of Chicago. She was an Assistant Professor at Duke University from 2011-2014, and an Assistant, Associate, and then Full Professor at Princeton University in Computer Science from 2014-2022. She has worked at Jet Propulsion Labs, Google Research, 23andMe, and Genomics plc. In her career, she received an NSF GRFP, the Google Anita Borg Scholarship, the SMBE Walter M. Fitch Prize (2004), a Sloan Faculty Fellowship, an NSF CAREER, and the ISCB Overton Prize (2021). Her research is focused on developing and applying models for structured biomedical data that capture patterns in the data, predict results of interventions to the system, assist with decision-making support, and prioritize experiments for design and engineering of biological systems.
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Dawson Engler
Associate Professor of Computer Science and of Electrical Engineering
BioEngler's research focuses both on building interesting software systems and on discovering and exploring the underlying principles of all systems.
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Daniel Bruce Ennis
Professor of Radiology (Veterans Affairs) and, by courtesy, of Bioengineering
Current Research and Scholarly InterestsThe Cardiac MRI Group seeks to invent and validate methods to quantify cardiac performance. We develop methods to measure cardiac structure (DWI/DTI), function (tagging and DENSE), flow (PC-MRI), and remodeling (diffusion, T1-mapping, fat-water mapping) for pediatrics and adults.
Fundamental to our research is a set of tools for numerically optimizing gradient waveforms, Bloch simulations, and patient-specific 3D-printed cardiovascular structures connected to computer controlled flow pumps. -
Anton Ermakov
Assistant Professor of Aeronautics and Astronautics and, by courtesy, of Geophysics and of Earth and Planetary Sciences
Current Research and Scholarly InterestsI am interested in the formation and evolution of the Solar System bodies and the ways we can constrain planetary interiors by geophysical measurements.
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Stefano Ermon
Associate Professor of Computer Science and Senior Fellow at the Woods Institute for the Environment
BioI am an Assistant Professor in the Department of Computer Science at Stanford University, where I am affiliated with the Artificial Intelligence Laboratory and a fellow of the Woods Institute for the Environment.
My research is centered on techniques for scalable and accurate inference in graphical models, statistical modeling of data, large-scale combinatorial optimization, and robust decision making under uncertainty, and is motivated by a range of applications, in particular ones in the emerging field of computational sustainability. -
Jonathan Fan
Associate Professor of Electrical Engineering
Current Research and Scholarly InterestsOptical engineering plays a major role in imaging, communications, energy harvesting, and quantum technologies. We are exploring the next frontier of optical engineering on three fronts. The first is new materials development in the growth of crystalline plasmonic materials and assembly of nanomaterials. The second is novel methods for nanofabrication. The third is new inverse design concepts based on optimization and machine learning.
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Judith Ellen Fan
Assistant Professor of Psychology, by courtesy, of Education and of Computer Science
BioI direct the Cognitive Tools Lab (https://cogtoolslab.github.io/) at Stanford University. Our lab aims to reverse engineer the human cognitive toolkit — in particular, how people use physical representations of thought to learn, communicate, and solve problems. Towards this end, we use a combination of approaches from cognitive science, computational neuroscience, and artificial intelligence.
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Shanhui Fan
Joseph and Hon Mai Goodman Professor of the School of Engineering, Senior Fellow at the Precourt Institute for Energy and Professor, by courtesy, of Applied Physics
BioFan's research interests are in fundamental studies of nanophotonic structures, especially photonic crystals and meta-materials, and applications of these structures in energy and information technology applications
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Charbel Farhat
Vivian Church Hoff Professor of Aircraft Structures and Professor of Aeronautics and Astronautics
Current Research and Scholarly InterestsCharbel Farhat and his Research Group (FRG) develop mathematical models, advanced computational algorithms, and high-performance software for the design, analysis, and digital twinning of complex systems in aerospace, marine, mechanical, and naval engineering. They contribute major advances to Simulation-Based Engineering Science. Current engineering foci in research are on reliable autonomous carrier landing in rough seas; dissipation of vertical landing energies through structural flexibility; nonlinear aeroelasticity of N+3 aircraft with High Aspect Ratio (HAR) wings; pulsation and flutter of a parachute; pendulum motion in main parachute clusters; coupled fluid-structure interaction (FSI) in supersonic inflatable aerodynamic decelerators for Mars landing; flight dynamics of hypersonic systems and their trajectories; and advanced digital twinning. Current theoretical and computational emphases in research are on high-performance, multi-scale modeling for the high-fidelity analysis of multi-component, multi-physics problems; discrete-event-free embedded boundary methods for CFD and FSI; efficient Bayesian optimization using physics-based surrogate models; modeling and quantifying model-form uncertainty; probabilistic, physics-based machine learning; mechanics-informed artificial neural networks for data-driven constitutive modeling; and efficient nonlinear projection-based model order reduction for time-critical applications such as design, active control, and digital twinning.
