School of Engineering
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Assistant Professor of Electrical Engineering and, by courtesy, of Materials Science and 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.
Director, Edward L. Ginzton Laboratory, Professor of Electrical Engineering, Senior Fellow at the Precourt Institute for Energy and Professor, by courtesy, of Applied Physics
BioFan's research involves the theory and simulations of photonic and solid-state materials and devices; photonic crystals; nano-scale photonic devices and plasmonics; quantum optics; computational electromagnetics; parallel scientific computing.
Vivian Church Hoff Professor of Aircraft Structures, Professor of Mechanical Engineering and Director of the Army High Performance Computing Research Center
Current Research and Scholarly InterestsCharbel Farhat and his Research Group (FRG) develop mathematical models, advanced computational algorithms, and high-performance software for the design and analysis 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 the nonlinear aeroelasticity and flight dynamics of Micro Aerial Vehicles (MAVs) with flexible flapping wings and N+3 aircraft with High Aspect Ratio (HAR) wings, layout optimization and additive manufacturing of wing structures, supersonic inflatable aerodynamic decelerators for Mars landing, and the reliable automated carrier landing via model predictive control. Current theoretical and computational emphases in research are on high-performance, multi-scale modeling for the high-fidelity analysis of multi-physics problems, high-order embedded boundary methods, uncertainty quantification, probabilistic machine learning, and efficient projection-based model order reduction as well as other forms of physics-based machine learning for time-critical applications such as design, active control, and digital twins.
BioDr. Rainer Fasching is a technology executive and a consulting associate professor at Stanford University, where he teaches advanced electrochemical energy storage and sensor technologies. He has over 20 years of experience in electrochemical devices, micro fabrication technologies, and industrial product development. His work has been centered on the physics, materials and fabrication technologies of electrochemical systems such as sensors, batteries and associated materials, and fuel cells. Currently he has been leading the development of advanced energy storage technologies from concept to product at top tier startup companies. He holds over 30 issued and/or published patents and has authored more than 60 publications.
Assistant Professor of Computer Science
BioKayvon Fatahalian is an assistant professor of Computer Science at Stanford University. His students work on visual computing systems projects, including large-scale video analytics, programming systems for video data mining, compilation techniques for optimizing image processing pipelines, and systems for real-time 3D graphics.
Professor of Computer Science
BioFedkiw's research is focused on the design of new computational algorithms for a variety of applications including computational fluid dynamics, computer graphics, and biomechanics.