School of Engineering
Showing 1-100 of 568 Results
-
Maneesh Agrawala
Forest Baskett Professor in the School of Engineering and Professor, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsComputer Graphics, Human Computer Interaction and Visualization.
-
Geun Ho Ahn
Ph.D. Student in Electrical Engineering, admitted Autumn 2018
Masters Student in Electrical Engineering, admitted Autumn 2020BioI am a PhD candidate in Electrical Engineering working at Professor Jelena Vuckovic's Nanoscale Quantum Photonics Laboratory. My research interests are computational optimizations of photonic devices and quantum technologies made from nanoscale fabrications.
-
Rehman Ali
Ph.D. Student in Electrical 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
-
Amin Arbabian
Associate Professor of Electrical Engineering
Current Research and Scholarly InterestsMy group's research covers RF circuits and system design for (1) biomedical, (2) sensing, and (3) Internet of Things (IoT) applications.
-
Serhat Arslan
Ph.D. Student in Electrical Engineering, admitted Autumn 2018
Current Research and Scholarly InterestsNetwork intelligence
There are 2 main aspects of network management:
Sensing
- Collecting useful and enough amount of information from the network is essential for modern, data-centric decision processes to work well.
Frameworks such as In-band Network Telemetry could be utilized to collect precise information on every single packet in the network.
Control
- Modern data science methodologies allow engineers to infer about the state of the network.
Naturally, the next step is to design tailored control algorithms that would utilize available resources the best.
Potential methods include, but not limited to, machine learning algorithms and control theory. -
Richard Bahr
Adjunct Professor, Electrical Engineering
BioAcademic experience:
Presently advising the Stanford SystemX Alliance, and the EE/CS AHA! Research center as an adjunct prof. Formerly the executive director of the SystemX Alliance, and a consulting professor at Stanford.
Commercial experience:
Presently an advisor, consultant and mentor to a number of startup companies primarily in the computing and wireless spaces. Formerly the SrVP responsible for Wi-Fi technology at Qualcomm, and before that the engineering executive responsible for the MIPS microprocessor and Cray supercomputer development at SGI.
Education: BSEE and MSEE from MIT.
For more extensive background, please consult my linked in profile: https://www.linkedin.com/in/rickbahr. -
Nicholas Bambos
Richard W. Weiland Professor in the School of Engineering and Professor of Electrical Engineering
BioNick Bambos is a Professor at Stanford University, having a joint appointment in the Department of Electrical Engineering and the Department of Management Science & Engineering. He heads the Network Architecture and Performance Engineering research group at Stanford, conducting research in wireless network architectures, the Internet infrastructure, packet switching, network management and information service engineering, engaged in various projects of his Network Architecture Laboratory (NetLab). His current technology research interests include high-performance networking, autonomic computing, and service engineering. His methodological interests are in network control, online task scheduling, queueing systems and stochastic processing networks.
He has graduated over 20 Ph.D. students, who are now at leadership positions in academia (Stanford, CalTech, Michigan, GaTech, NYU, UBC, etc.) and the information technology industry (Cisco, Broadcom, IBM Labs, Qualcomm, Nokia, MITRE, Sun Labs, ST Micro, Intel, Samsung, TI, etc.) or have become successful entrepreneurs. From 1999 to 2005 he served as the director of the Stanford Networking Research Center, a major partnership/consortium between Stanford and information technology industries, involving tens of corporate members, faculty and doctoral students. He is now heading a new research initiative at Stanford on Networked Information Service Engineering.
He is on the Editorial Boards of several research journals and serves on various international technical committees and review panels for networking research and information technologies. He has been serving on the boards of various start-up companies in the Silicon Valley, consults on high technology development and management matters, and has served as lead expert witness in high-profile patent litigation cases in networking and computing. -
Mohsen Bayati
Associate Professor of Operations, Information and Technology at the Graduate School of Business and, by courtesy, of Electrical Engineering
Current Research and Scholarly Interests1) Healthcare management: I am interested in improving healthcare delivery using data-driven modeling and decision-making.
2) Network models and message-passing algorithms: I work on graphical modeling ideas motivated from statistical physics and their applications in statistical inference.
3) Personalized decision-making: I work on machine learning and statistical challenges of personalized decision-making. The problems that I have worked on are primarily motivated by healthcare applications. -
Stacey Bent
Vice Provost for Graduate Education and Postdoctoral Affairs, Jagdeep and Roshni Singh Professor in the School of Engineering, and Professor, by courtesy, of Materials Science & Engineering, of Electrical Engineering and of Chemistry
BioThe research in the Bent laboratory is focused on understanding and controlling surface and interfacial chemistry and applying this knowledge to a range of problems in semiconductor processing, micro- and nano-electronics, nanotechnology, and sustainable and renewable energy. Much of the research aims to develop a molecular-level understanding in these systems, and hence the group uses of a variety of molecular probes. Systems currently under study in the group include functionalization of semiconductor surfaces, mechanisms and control of atomic layer deposition, molecular layer deposition, nanoscale materials for light absorption, interface engineering in photovoltaics, catalyst and electrocatalyst deposition.
-
Nikhil Bhagdikar
Ph.D. Student in Electrical Engineering, admitted Autumn 2014
BioEase of implementation and energy efficiency are critical for modern digital ICs. I am researching techniques to improve energy efficiency without compromising on performance or silicon area, especially for CGRA.
-
Kwabena Boahen
Professor of Bioengineering, of Electrical Engineering and, by courtesy, of Computer Science
Current Research and Scholarly InterestsLarge-scale models of sensory, perceptual and motor systems
-
Dan Boneh
Cryptography Professor, Professor of Electrical Engineering and Senior Fellow at the Freeman Spogli Institute for International Studies
BioProfessor Boneh heads the applied cryptography group and co-direct the computer security lab. Professor Boneh's research focuses on applications of cryptography to computer security. His work includes cryptosystems with novel properties, web security, security for mobile devices, and cryptanalysis. He is the author of over a hundred publications in the field and is a Packard and Alfred P. Sloan fellow. He is a recipient of the 2014 ACM prize and the 2013 Godel prize. In 2011 Dr. Boneh received the Ishii award for industry education innovation. Professor Boneh received his Ph.D from Princeton University and joined Stanford in 1997.
-
Stephen Boyd
Samsung Professor in the School of Engineering and Professor, by courtesy, of Computer Science and of Management Science and Engineering
BioStephen P. Boyd is the Samsung Professor of Engineering, and Professor of Electrical Engineering in the Information Systems Laboratory at Stanford University. He has courtesy appointments in the Department of Management Science and Engineering and the Department of Computer Science, and is member of the Institute for Computational and Mathematical Engineering. His current research focus is on convex optimization applications in control, signal processing, machine learning, and finance.
Professor Boyd received an AB degree in Mathematics, summa cum laude, from Harvard University in 1980, and a PhD in EECS from U. C. Berkeley in 1985. In 1985 he joined Stanford's Electrical Engineering Department. He has held visiting Professor positions at Katholieke University (Leuven), McGill University (Montreal), Ecole Polytechnique Federale (Lausanne), Tsinghua University (Beijing), Universite Paul Sabatier (Toulouse), Royal Institute of Technology (Stockholm), Kyoto University, Harbin Institute of Technology, NYU, MIT, UC Berkeley, CUHK-Shenzhen, and IMT Lucca. He holds honorary doctorates from Royal Institute of Technology (KTH), Stockholm, and Catholic University of Louvain (UCL).
Professor Boyd is the author of many research articles and four books: Introduction to Applied Linear Algebra: Vectors, Matrices, and Least-Squares (with Lieven Vandenberghe, 2018), Convex Optimization (with Lieven Vandenberghe, 2004), Linear Matrix Inequalities in System and Control Theory (with El Ghaoui, Feron, and Balakrishnan, 1994), and Linear Controller Design: Limits of Performance (with Craig Barratt, 1991). His group has produced many open source tools, including CVX (with Michael Grant), CVXPY (with Steven Diamond) and Convex.jl (with Madeleine Udell and others), widely used parser-solvers for convex optimization.
Professor Boyd has received many awards and honors for his research in control systems engineering and optimization, including an ONR Young Investigator Award, a Presidential Young Investigator Award, and the AACC Donald P. Eckman Award. In 2013, he received the IEEE Control Systems Award, given for outstanding contributions to control systems engineering, science, or technology. In 2012, Michael Grant and he were given the Mathematical Optimization Society's Beale-Orchard-Hays Award, for excellence in computational mathematical programming. He is a Fellow of the IEEE, SIAM, and INFORMS, a Distinguished Lecturer of the IEEE Control Systems Society, a member of the US National Academy of Engineering, a foreign member of the Chinese Academy of Engineering, and a foreign member of the National Academy of Engineering of Korea. He has been invited to deliver more than 90 plenary and keynote lectures at major conferences in control, optimization, signal processing, and machine learning.
He has developed and taught many undergraduate and graduate courses, including Signals & Systems, Linear Dynamical Systems, Convex Optimization, and a recent undergraduate course on Matrix Methods. His graduate convex optimization course attracts around 300 students from more than 20 departments. In 1991 he received an ASSU Graduate Teaching Award, and in 1994 he received the Perrin Award for Outstanding Undergraduate Teaching in the School of Engineering. In 2003, he received the AACC Ragazzini Education award, for contributions to control education, with citation: “For excellence in classroom teaching, textbook and monograph preparation, and undergraduate and graduate mentoring of students in the area of systems, control, and optimization.” In 2016 he received the Walter J. Gores award, the highest award for teaching at Stanford University. In 2017 he received the IEEE James H. Mulligan, Jr. Education Medal, for a career of outstanding contributions to education in the fields of interest of IEEE, with citation "For inspirational education of students and researchers in the theory and application of optimization." -
Iliana Erteza Bray
Ph.D. Student in Electrical Engineering, admitted Autumn 2017
Masters Student in Electrical Engineering, admitted Winter 2018BioIliana is a fourth year Ph.D. candidate in Electrical Engineering. She received her BS in Electrical Engineering with honors from Stanford in 2017 and was awarded the Firestone Medal for Excellence in Undergraduate Research for her honors thesis. She is an NSF GRFP fellowship recipient (2017).
Iliana's long-term research interests involve combining electrical engineering and neuroscience to further our understanding of motor control and one day incorporate this new knowledge into improved brain-computer interfaces or enhanced rehabilitation for clinical populations with compromised mobility. -
Emmanuel Candes
Barnum-Simons Chair in Math and Statistics, and Professor of Statistics and, by courtesy, of Electrical Engineering
BioEmmanuel Candès is the Barnum-Simons Chair in Mathematics and Statistics, a professor of electrical engineering (by courtesy) and a member of the Institute of Computational and Mathematical Engineering at Stanford University. Earlier, Candès was the Ronald and Maxine Linde Professor of Applied and Computational Mathematics at the California Institute of Technology. His research interests are in computational harmonic analysis, statistics, information theory, signal processing and mathematical optimization with applications to the imaging sciences, scientific computing and inverse problems. He received his Ph.D. in statistics from Stanford University in 1998.
Candès has received several awards including the Alan T. Waterman Award from NSF, which is the highest honor bestowed by the National Science Foundation, and which recognizes the achievements of early-career scientists. He has given over 60 plenary lectures at major international conferences, not only in mathematics and statistics but in many other areas as well including biomedical imaging and solid-state physics. He was elected to the National Academy of Sciences and to the American Academy of Arts and Sciences in 2014. -
Alexander Carsello
Ph.D. Student in Electrical Engineering, admitted Autumn 2017
BioAlex is currently a Ph.D. student in Electrical Engineering advised by Mark Horowitz and affiliated with the AHA! Agile Hardware Center. He is interested in reconfigurable computing, domain-specific architectures for image processing, and hardware design methodology. He is currently working within the AHA Agile Hardware Project on a next-generation CGRA (coarse-grained reconfigurable architecture) chip generator. Alex received a B.S. in Electrical and Computer Engineering from Washington University in St. Louis in 2017.
-
Shubham Chandak
Ph.D. Student in Electrical Engineering, admitted Autumn 2016
Current Research and Scholarly InterestsDNA storage, genomic data compression, information theory, machine learning
-
E.J. Chichilnisky
John R. Adler Professor, Professor of Neurosurgery and of Ophthalmology and, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsFunctional circuitry of the retina and design of retinal prostheses
-
Jun-Chau Chien
Research Engineer
BioJun-Chau Chien received the B.S. and M.S. degrees in Electrical Engineering from National Taiwan University in 2004 and 2006, respectively, and the Ph.D. degree in Electrical Engineering and Computer Sciences from University of California, Berkeley, in 2015. He is currently a post-doctoral research associate at Stanford University. He has held industrial positions at InvenSense, Xilinx, and HMicro working on mixed-signal integrated circuits for inertial sensors and wireline/wireless transceivers. He is broadly interested in innovative biotechnology for point-of-care diagnostics and medical imaging with emphasis on silicon-based approaches.
-
Benjamin Choi
Student Researcher, Electrical Engineering
Undergraduate, Electrical EngineeringBioResearch interests: smart cities, sustainable infrastructure
Other interests: plants, dogs, guitar
Website: https://benchoi.me -
Srabanti Chowdhury
Associate Professor of Electrical Engineering and Center Fellow, by courtesy, at the Precourt Institute for Energy
Current Research and Scholarly InterestsWide bandap materials & devices for RF, Power and energy efficient electronics
-
John M. Cioffi
Hitachi America Professor in the School of Engineering, Emeritus
BioJohn M. Cioffi taught Stanford's graduate electrical engineering course sequence in digital communications for over 20 years from 1986 to 2008, when he retired to emeritus. Cioffi's research interests were in the theory of transmitting the highest possible data rates on a number of different communications channels, many of which efforts were spun out of Stanford through he and/or his many former PhD students to companies, most notably including the basic designed used worldwide on more than 500 million DSL connections. Cioffi also over saw the prototype developments for the worlds first cable modem and digital-audio broadcast system. Cioffi pioneering the use of remote management algorithms to improve (over the internet or cloud) both wireline (DSL) and wireless (Wi-Fi) physical-layer transmission performance, an area often known as Dynamic Spectrum Management or Dynamic Line Management. Cioffi was co-inventer on basic patents for vectored DSL transmission and optimized MIMO wireless transmission. In his early career, Cioffi developed the worlds first full-duplex voiceband data modem while at Bell Laboratories, and the worlds first adaptively equalized disk read channel while at IBM. His courses and research projects over the years centered on these areas.
-
Sigrid Close
Associate Professor of Aeronautics and Astronautics and, by courtesy, of Electrical Engineering
BioProf. Close's research involves space weather detection and modeling for improved spacecraft designs, and advanced signal processing and electromagnetic wave interactions with plasma for ground-to-satellite communication systems. These topics fall under the Space Situational Awareness (SSA) umbrella that include environmental remote sensing using satellite systems and ground-based radar. Her current efforts are the MEDUSSA (Meteoroid, Energetics, and Debris Understanding for Space Situational Awareness) program, which uses dust accelerators to understand the effects of hypervelocity particle impacts on spacecraft along with Particle-In-Cell simulations, and using ground-based radars to characterize the space debris and meteoroid population remotely. She also has active programs in hypersonic plasmas associated with re-entry vehicles.
-
Daniel Norbert Congreve
Assistant Professor of Electrical Engineering
BioDan Congreve received his B.S. and M.S. from Iowa State in 2011, working with Vik Dalal studying defect densities of nano-crystalline and amorphous silicon. He received his PhD from MIT in 2015, studying under Marc Baldo. His thesis work focused on photonic energy conversion using singlet fission and triplet fusion as a downconverting and upconverting process, respectively. He joined the Rowland Institute at Harvard University in August 2016, where his current research efforts focus on controlling light and energy at the nanoscale. He will start as an Assistant Professor of Electrical Engineering at Stanford in Fall 2020.
-
Riley Culberg
Ph.D. Student in Electrical Engineering, admitted Autumn 2019
BioMy research focuses on resolving the near-surface and internal structure of the continental ice sheets in Greenland and Antarctica using airborne ice penetrating radar systems. I am particularly interested in understanding the coupling between firn structure and near-surface hydrology in Greenland, the evolution of this system in a warming climate, and its influence on the large scale ice sheet mass balance and hydrology. Additionally, I am interested in deep englacial structure as a reflection of past climate processes and ice sheet age structure. My approach to these questions involves the synthesis of electromagnetic theory, radar signal and system constraints, and in-situ observations to develop both forward and inverse methods that link physical conditions of interest within the ice sheets to their expression in radar sounding data. Applying these tools to the analysis of radar sounding data allows me to place observational constraints on state of the englacial system at scales and resolutions that bridge the gap between field measurements and numerical models. In addition, I have applied some of these same techniques to study the optimal system design parameters for future high altitude or satellite-based radar systems.
