School of Engineering
Showing 701-800 of 1,923 Results
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Doug James
LeRa Professor and Professor, by courtesy, of Music
Current Research and Scholarly InterestsComputer graphics & animation, physics-based sound synthesis, computational physics, haptics, reduced-order modeling
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Atindra Jha
Ph.D. Student in Electrical Engineering, admitted Autumn 2026
Research Engineer, Program-Leskovec, J.BioI am a PhD student advised by Jure Leskovec and Percy Liang. I work on efficient and performant large-scale distributed data processing (currently, agentic and mixed-modal inference), natural language processing, and machine learning. I also work with Stephanie Wang, Baris Kasikci, and Luke Zettlemoyer at the University of Washington. I completed by B.S. and M.S. in Computer Science at Stanford, advised by Prof. Mark Horowitz, and affiliated with the Portal Center, AHA! Agile Hardware Center, and the Stanford VLSI Group.
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Enyi Jiang
Graduate Visiting Researcher Student, Computer Science
BioI am a third-year Computer Science Ph.D. student at the University of Illinois at Urbana-Champaign, advised by Prof. Sanmi Koyejo and Prof. Nancy Amato. I am broadly interested in trustworthy machine learning, especially in AI safety and alignment.
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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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Kshitij Kant
Undergraduate, Computer Science
Undergraduate, EconomicsBioHi! I'm Kshitij, and I am pursuing Economics and Computer Science at Stanford University. I'm interested in understanding the intersection of technology and economic systems, and how they shape our world. I am happy to collaborate on ideas or create something big! Feel free to reach out to me on kkant@stanford.edu.
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Zerina Kapetanovic
Assistant Professor of Electrical Engineering and, by courtesy, of Computer Science and of Geophysics
BioZerina Kapetanovic is an Assistant Professor in the Department of Electrical Engineering at Stanford University working in the area of low-power wireless communication, sensing, and Internet of Things (IoT) systems. Prior to starting at Stanford, Kapetanovic was a postdoctoral researcher at Microsoft Research in the Networking Research Group and Research for Industry Group.
Kapetanovic's research has been recognized by the Yang Research Award, the Distinguished Dissertation Award from the University of Washington. She also received the Microsoft Research Distinguished Dissertation Grant and was selected to attend the 2020 UC Berkeley Rising Stars in EECS Workshop. Kapetanovic completed her PhD in Electrical Engineering from the University of Washington in 2022. -
Shraman Kar
Undergraduate, Computer Science
BioShraman is passionate about building technology projects using artificial intelligence and state-of-the-art large language models to solve problems of the community and the environment. Shraman's passion project, Foodle (www.thefoodle.org) built on technology and artificial intelligence could make a difference in solving hunger and food waste at the same time. He wanted to share his knowledge and ideas with as many youths as possible so that together they can build technology products for the communities.
To unleash the potential of AI for social good Shraman cofounded a 501(c)(3) organization Community AI (www.thecommunityai.org) in the year 2000. They created a customized course of Machine Learning suitable for a wide range of school-going youth and delivered via free camps. The camps became very popular and they could mentor students from 58 countries and all 50 US states. The members have several projects to help the community and the environment- ranging from automatic trash segregation to detecting wildfire before it happens and many more. To encourage more students to build AI-driven projects we provided funds/prizes via the AI Fair called Sustainability and Community AI Fair (www.communityaifair.com). -
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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Monroe Kennedy III
Assistant Professor of Mechanical Engineering and, by courtesy, of Computer Science
Current Research and Scholarly InterestsMy research focus is to develop technology that improves everyday life by anticipating and acting on the needs of human counterparts. My research can be divided into the following sub-categories: robotic assistants, connected devices and intelligent wearables. My Assistive Robotics and Manipulation lab focuses heavily on both the analytical and experimental components of assistive technology design.
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Oussama Khatib
Weichai Professor and Professor, by courtesy, of Electrical Engineering
BioRobotics research on novel control architectures, algorithms, sensing, and human-friendly designs for advanced capabilities in complex environments. With a focus on enabling robots to interact cooperatively and safely with humans and the physical world, these studies bring understanding of human movements for therapy, athletic training, and performance enhancement. Our work on understanding human cognitive task representation and physical skills is enabling transfer for increased robot autonomy. With these core capabilities, we are exploring applications in healthcare and wellness, industry and service, farms and smart cities, and dangerous and unreachable settings -- deep in oceans, mines, and space.
