School of Engineering
Showing 1-100 of 144 Results
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Andrei Kanavalau
Ph.D. Student in Electrical Engineering, admitted Autumn 2020
BioPhD candidate in Electrical Engineering at Stanford working across LLMs/Transformers, constrained optimization, and control.
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Hangoo Kang
Masters Student in Computer Science, admitted Autumn 2025
BioHangoo Kang is a computer science MS student at Stanford University with a strong interest in building trustworthy and efficient AI systems. He earned his B.S. in Computer Science from the University of Illinois Urbana-Champaign (UIUC). His academic and research pursuits span reinforcement learning (RL), reinforcement learning from human feedback (RLHF), agentic AI, large language models (LLMs), and multi-modal models.
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Shreyas Kar
Masters Student in Computer Science, admitted Autumn 2023
BioShreyas is an undergraduate Computer Science and Math (double major) student and a researcher at Stanford Partnership in AI-Assisted Care (PAC - https://www.med.stanford.edu/pacresearch.html) group, as part of Stanford Vision and Learning (SVL) lab under Professor Fei-Fei Li and Professor Ehsan Adeli. He is interested in using Artificial Intelligence & Technology to better our community and environment. He founded a 501(c)(3) non-profit organization, Community AI (https://www.thecommunityai.org/), to unleash the power of artificial intelligence for social good and empower youth. Earlier, he worked for the PORTAL group at Harvard Medical School as a member of Research Science Institute (RSI). His research there focussed on quantifying the impact of EHR-Discontinuity on prediction modeling algorithms. His LinkedIn profile is: https://www.linkedin.com/in/shreyas-kar/
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Doyeon Kim
Masters Student in Bioengineering, admitted Autumn 2025
Current Research and Scholarly InterestsNeuroscience, systems neuroscience, memory dynamics
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Kyung Geun Kim
Ph.D. Student in Bioengineering, admitted Autumn 2024
Masters Student in Bioengineering, admitted Spring 2026BioKyung Geun Kim is a Bioengineering PhD candidate in the Druckmann Lab at Stanford. He is interested in developing interpretable computational methods to study how neural population dynamics across brain regions support decision making and flexible behavior. Before Stanford, he earned his BS and MS in Electrical Engineering and Computer Sciences from UC Berkeley and worked in industry as a research scientist developing medical AI for clinical decision support.
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MinJae Kim
Ph.D. Student in Materials Science and Engineering, admitted Autumn 2025
Current Research and Scholarly InterestsMetasurfaces, Bioimaging, Optoelectronic materials and devices
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Moo Jin Kim
Ph.D. Student in Computer Science, admitted Autumn 2023
BioMoo Jin Kim is a Ph.D. student in Computer Science at Stanford University (2023 – present) who conducts research in end-to-end vision-based robotic manipulation.
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Sam Kipper
Ph.D. Student in Civil and Environmental Engineering, admitted Summer 2026
BioMy name is Samantha Kipper, and I am a graduate student in Civil and Environmental Engineering. My research focuses on offshore wind energy, and I aim to make the world a better place through technical, sustainable energy solutions.
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Yun-Dam Ko
Ph.D. Student in Civil and Environmental Engineering, admitted Autumn 2024
BioYun-Dam Ko's research focuses on combining data-driven solutions with building physics to enhance the sustainability of the urban built environment. His recent work leverages AI to optimize building energy performance, with a specific focus on intelligent HVAC system control and advanced Building Energy Modeling. Bridging research and practice, he previously worked at a startup where he developed and deployed AI solutions to improve building energy efficiency at scale.
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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.
