School of Engineering


Showing 1-10 of 388 Results

  • Brian Hargreaves

    Brian Hargreaves

    Associate Professor of Radiology (Radiological Sciences Laboratory) and, by courtesy, of Electrical Engineering and of Bioengineering

    Current Research and Scholarly InterestsI am interested in magnetic resonance imaging (MRI) applications including cardiovascular, abdominal, breast and musculoskeletal imaging. These applications require development of faster and more efficient MRI methods that provide improved diagnostic contrast compared with current methods. My work includes novel excitation schemes, efficient imaging methods and reconstruction tools. Please see my research site (above) for most up-to-date information.

  • Brad Osgood

    Brad Osgood

    Professor of Electrical Engineering and, by courtesy, of Education

    BioOsgood is a mathematician by training and applies techniques from analysis and geometry to various engineering problems. He is interested in problems in imaging, pattern recognition, and signal processing.

  • Debbie Senesky

    Debbie Senesky

    Assistant Professor of Aeronautics and Astronautics and, by courtesy, of Electrical Engineering

    BioProfessor Senesky's research is centered on the development of micro- and nano-systems for operation within extreme harsh environments. Her laboratory (EXtreme Environment Microsystems Laboratory, XLab) is researching the synthesis of temperature tolerant, chemically resistant, and radiation-hardened wide bandgap semiconductor thin films and nanostructures. These new material sets serve as a platform for the realization of sensor, actuator, and electronic components that can operate and collect data under the most hostile conditions. More specifically, smart and adaptable structures for extreme environments are enabled through the technology developed in her laboratory. Her research efforts support a variety of applications including deep space systems, hypersonic aircrafts, combustion monitoring and subsurface monitoring.

  • Boris Murmann

    Boris Murmann

    Professor of Electrical Engineering

    BioBoris Murmann is a Professor of Electrical Engineering at Stanford University. He joined Stanford in 2004 after completing his Ph.D. degree in electrical engineering at the University of California, Berkeley in 2003. From 1994 to 1997, he was with Neutron Microelectronics, Germany, where he developed low-power and smart-power ASICs in automotive CMOS technology. Since 2004, he has worked as a consultant with numerous Silicon Valley companies. Dr. Murmann’s research interests are in mixed-signal integrated circuit design, with special emphasis on sensor interfaces, data converters and custom circuits for machine learning. In 2008, he was a co-recipient of the Best Student Paper Award at the VLSI Circuits Symposium and a recipient of the Best Invited Paper Award at the IEEE Custom Integrated Circuits Conference (CICC). He received the Agilent Early Career Professor Award in 2009 and the Friedrich Wilhelm Bessel Research Award in 2012. He has served as an Associate Editor of the IEEE Journal of Solid-State Circuits, as well as the Data Converter Subcommittee Chair and the Technical Program Chair of the IEEE International Solid-State Circuits Conference (ISSCC). He is the founding faculty co-director of the Stanford SystemX Alliance and the faculty director of Stanford's System Prototyping Facility (SPF). He is a Fellow of the IEEE.

  • Marco Pavone

    Marco Pavone

    Assistant Professor of Aeronautics and Astronautics and, by courtesy, of Electrical Engineering

    BioDr. Marco Pavone is an Assistant Professor of Aeronautics and Astronautics at Stanford University, where he also holds courtesy appointments in the Department of Electrical Engineering, in the Institute for Computational and Mathematical Engineering, and in the Information Systems Laboratory. He is a Research Affiliate at the NASA Jet Propulsion Laboratory (JPL), California Institute of Technology. Before joining Stanford, he was a Research Technologist within the Robotics Section at JPL. He received a Ph.D. degree in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 2010. Dr. Pavone’s areas of expertise lie in the fields of controls and robotics.

    Dr. Pavone is a recipient of a NASA Early Career Faculty award, a Hellman Faculty Scholar Award, and was named NASA NIAC Fellow in 2011. At JPL, Dr. Pavone worked on the end-to-end optimization of the mission architecture for the Mars sample return mission. He has designed control algorithms for formation flying that have been successfully tested on board the International Space Station.

    Dr. Pavone is the Director of the Autonomous Systems Laboratory (ASL). The goal of ASL is the development of methodologies for the analysis, design, and control of autonomous systems, with a particular emphasis on large-scale robotic networks and autonomous aerospace vehicles. The lab combines expertise from control theory, robotics, optimization, and operations research to develop the theoretical foundations for networked autonomous systems operating in uncertain, rapidly-changing, and potentially adversarial environments. Theoretical insights are then used to devise practical, computationally-efficient, and provably-correct algorithms for field deployment. Applications include robotic transportation networks, sensor networks, agile control of spacecraft during proximity operations, and mobility platforms for extreme planetary environments. Collaborations with NASA centers are a key component of the research portfolio.

  • Rehman Ali

    Rehman Ali

    Ph.D. Student in Electrical Engineering, admitted Autumn 2017
    Masters Student in Computational and Mathematical Engineering, admitted Autumn 2017

    BioRehman Ali received the B.S. degree in biomedical engineering from Georgia Institute of Technology in 2016. He is currently an NDSEG fellow, completing a M.S. in Computational & Mathematical Engineering and pursuing a Ph.D. in Electrical Engineering at Stanford. His research interests include signal processing, inverse problems, computational modeling of acoustics, and real-time beamforming algorithms. His current research is developing accurate and spatially resolved speed-of-sound imaging in tissue based on phase aberration correction, spatial coherence, and computed tomography