School of Engineering
Showing 1-100 of 407 Results
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Phil Adamson
Ph.D. Student in Electrical Engineering, admitted Autumn 2020
Masters Student in Electrical Engineering, admitted Winter 2022BioPhil is an Electrical Engineering PhD student conducting inter-disciplinary medical imaging research in the Radiological Sciences Laboratory in the Stanford Medicine Department of Radiology. His research interests include MR methods for metabolic imaging, particularly Deuterium Metabolic Imaging (DMI), and Deep Learning methods for solving inverse problems in limited data regimes with applications to MRI.
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Geun Ho Ahn
Ph.D. Student in Electrical Engineering, admitted Autumn 2018
BioI 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.
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Nancy Ammar
Ph.D. Student in Electrical Engineering, admitted Autumn 2021
BioNancy Y. Ammar received her B.Sc. degree (with honors) in electronics and communication engineering from Ain Shams University, Cairo, Egypt, in 2019. In her senior year, she worked as an undergraduate Research Assistant in the Microwaves and Antenna Research Lab at Ain Shams University. She worked as an IC design consultant at Siemens EDA (Mentor Graphics previously).
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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. -
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.
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Iliana Erteza Bray
Ph.D. Student in Electrical Engineering, admitted Autumn 2017
BioIliana is a fifth year Ph.D. candidate in Electrical Engineering. She has been awarded the Stanford Gerald J. Lieberman Fellowship (2022), the American Heart Association Predoctoral Fellowship (2021), the Cadence Women in Technology Scholarship (2021), and the NSF Graduate Research Fellowship (2017). 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.
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. -
Chris Calloway
Masters Student in Electrical Engineering, admitted Autumn 2021
Biohttps://www.linkedin.com/in/christopher-calloway-5447a1166/
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Alex 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.
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Po-Han Chen
Ph.D. Student in Electrical Engineering, admitted Winter 2021
Masters Student in Electrical Engineering, admitted Winter 2022BioPo-Han Chen is an EE Ph.D. student at Stanford University supervised by Prof. Priyanka Raina. He received his B.S. in Electrical Engineering and Computer Science (EECS) and M.S. in Electrical Engineering from National Tsing Hua University (Taiwan) in 2016 and 2018 respectively. Before joining Stanford, he was a digital circuit designer at MediaTek where he worked on developing hardware architectures of image processing pipeline. He is interested in designing hardware accelerators. Most of his previous works were related to computational photography algorithms such as digital refocusing. Currently, He is focusing on analyzing and designing architecture of CGRAs to create high-performance, energy-efficient, and reconfigurable computing platforms.
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Benjamin Choi
Masters Student in Electrical Engineering, admitted Autumn 2019
BioWebsite: benchoi.me
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Jasmine Cox
Ph.D. Student in Electrical Engineering, admitted Autumn 2020
BioJasmine Cox is a PhD candidate in Electrical Engineering. She received her B.S. in Electrical Engineering with a minor in Applied Mathematics from Boise State University in 2020. During her undergraduate academic career, Jasmine was a Ronald E. McNair Scholar and a member of the Advanced Nanomaterials and Manufacturing Laboratory focusing on additive manufacturing of flexible hybrid electronics. Her current research as a member of Prof. Debbie G. Senesky’s group, EXtreme Environment Microsystems Lab (XLab), explores the synthesis, fabrication, and characterization of devices and materials in extreme environments that can be found in space.
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Yiwen Dong
Ph.D. Student in Civil and Environmental Engineering, admitted Autumn 2020
Ph.D. Minor, Electrical EngineeringBioYiwen Dong is a Ph.D. student in the Department of Civil and Environmental Engineering at Stanford University, advised by Prof. Hae Young Noh. Her research interest is human behavior characterization and health monitoring through their interactions with the physical structures. Her current work focuses on human and animal health monitoring through footstep/activity-induced structural vibrations.
While structures are traditionally considered as passive and indifferent, her works allow the structures to be both self-aware and user-aware. Yiwen developed systems that utilize the ambient structural vibrations to infer human behaviors and health states, which enables many smart building applications such as in-home patient monitoring and elder care, intruder prevention and occupant management, animal health monitoring and welfare. She strives for the next-generation intelligent infrastructures by exploring the potential of structural monitoring for human-centered purposes.
Yiwen has an interdisciplinary background in structural engineering, electrical engineering, and machine learning. Yiwen received her Master’s degree in Structural Engineering at Stanford University and her Bachelor’s degree in civil engineering at Nanyang Technological University. She won various awards (Best Paper Award, runner-ups in competitions) in ubiquitous computing and cyber-physical system conferences. She is passionate about combining the physical knowledge from structural dynamics, sensing approaches from cyber-physical systems, and data-driven models from machine learning to infer people’s characteristics, behavior patterns and health states.
