School of Engineering
Showing 1,251-1,300 of 2,952 Results
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Taeyoung Kong
Ph.D. Student in Electrical Engineering, admitted Autumn 2017
BioTaeyoung is a Ph.D. student at Stanford University working with prof. Mark Horowitz in VLSI group and he is currently working within the AHA Agile Hardware Project. He is interested in hardware accelerator for deep learning / image processing and hardware design methodology. Taeyoung received a B.S. in Electrical and Computer Engineering from Seoul National University in 2017, and M.S. in Electrical Engineering from Stanford University in 2020.
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Filippos Kostakis
Ph.D. Student in Energy Resources Engineering, admitted Winter 2020
Masters Student in Computer Science, admitted Autumn 2023Current Research and Scholarly InterestsMutlifidelity strategies for uncertainty quantification, data assimilation and optimization in oil and gas reservoirs.
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Kalhan Koul
Ph.D. Student in Electrical Engineering, admitted Autumn 2019
BioKalhan Koul is an EE Ph.D. student at Stanford University supervised by Prof. Priyanka Raina. Previously, he was a Digital Design Intern at Micron and Silicon Labs. He received a B.S. in Electrical Engineering Honors and a B.A. in Plan II Honors (Liberal Arts) from The University of Texas in 2018 and his M.S. in Electrical Engineering from Stanford University in 2021. During his PhD he has worked on three chip tapeouts. The first was Chimera, a DNN accelerator utilizing RRAM for low energy inference. The next was Amber, a coarse grained reconfigurable array (CGRA) optimized for image processing and machine learning applications. Finally, Kalhan led the tapeout of Onyx, a CGRA accelerating both dense and sparse kernels on the same fabric. His current research focuses on further improving the efficiency of the CGRA and extending its acceleration to end-to-end machine learning workloads.
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Parthiv Krishna
Masters Student in Computer Science, admitted Autumn 2020
BioI'm a student at Stanford with a passion for hardware and software, and aspirations to pursue a career in product innovation and entrepreneurship. I have experience with various robotics projects and have a particular interest in computer architecture for high-performance embedded computing. Outside of the classroom, I'm involved with the Stanford Harmonics a cappella group, the Stanford Ski Team, Stanford Student Robotics, and Delta Kappa Epsilon.
For my undergrad in Electrical Engineering major on the Hardware and Software track, I focused on computer systems and signal processing. I also completed a minor in Music, focusing on audio production and music theory. I found lots of interesting overlap between EE and Music, especially in the domain of signals.
For my Master's degree in Computer Science, I'm on the Systems track where I am studying computer architecture, compilers, and embedded systems. I am focusing my coursework and research towards areas like hardware/software co-design, efficient embedded architectures, and domain-specific hardware. -
Renesmee Kuo
Ph.D. Student in Electrical Engineering, admitted Autumn 2022
Masters Student in Electrical Engineering, admitted Autumn 2023BioRenesmee Kuo is an Electrical Engineering PhD candidate at Stanford University supported by NSF GRFP. She focuses on preclinical PET imaging for neuroinflammatory diseases and cancer in Prof. Michelle James' lab. She graduated from UC Berkeley with a BS in Bioengineering. Her research interests lie at the intersection of engineering and medicine. At UC Berkeley, she worked in Prof. Steve Conolly's lab on Magnetic Particle Imaging (MPI). She focused on tracking CAR-T cells in immunotherapy using high-resolution MPI tracers. She also focused on using commercially available high-resolution MPI tracers for early diagnosis of Pulmonary Embolisms and Cardiovascular disease in preclinical settings.
