School of Engineering
Showing 1-100 of 126 Results
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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, and is a Terman Faculty Fellow. 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. -
Shreyas Kar
Undergraduate, Computer Science
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.
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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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Fredrik Kjolstad
Assistant Professor of Computer Science
BioFredrik Kjolstad is an Assistant Professor in Computer Science at Stanford University. He works on topics in compilers, programming models, and systems, with an emphasis on compilers for sparse computing problems where we need to separate the algorithms from data representation, as well as fast compilers. He has received the NSF CAREER Award, the MIT EECS First Place George M. Sprowls PhD Thesis Award in Computer Science, the Rosing Award, an Adobe Fellowship, a Google Research Scholarship, and several best/distinguished paper awards.
Website: https://fredrikbk.com/ -
Donald Knuth
Fletcher Jones Professor of Computer Science, Emeritus
BioDonald Ervin Knuth is an American computer scientist, mathematician, and Professor Emeritus at Stanford University.
He is the author of the multi-volume work The Art of Computer Programming and has been called the "father" of the analysis of algorithms. He contributed to the development of the rigorous analysis of the computational complexity of algorithms and systematized formal mathematical techniques for it. In the process he also popularized the asymptotic notation. In addition to fundamental contributions in several branches of theoretical computer science, Knuth is the creator of the TeX computer typesetting system, the related METAFONT font definition language and rendering system, and the Computer Modern family of typefaces.
As a writer and scholar,[4] Knuth created the WEB and CWEB computer programming systems designed to encourage and facilitate literate programming, and designed the MIX/MMIX instruction set architectures. As a member of the academic and scientific community, Knuth is strongly opposed to the policy of granting software patents. He has expressed his disagreement directly to the patent offices of the United States and Europe. (via Wikipedia) -
Mykel Kochenderfer
Associate Professor of Aeronautics and Astronautics and, by courtesy, of Computer Science
BioMykel Kochenderfer is Associate Professor of Aeronautics and Astronautics at Stanford University. Prior to joining the faculty, he was at MIT Lincoln Laboratory where he worked on airspace modeling and aircraft collision avoidance, with his early work leading to the establishment of the ACAS X program. He received a Ph.D. from the University of Edinburgh and B.S. and M.S. degrees in computer science from Stanford University. Prof. Kochenderfer is the director of the Stanford Intelligent Systems Laboratory (SISL), conducting research on advanced algorithms and analytical methods for the design of robust decision making systems. Of particular interest are systems for air traffic control, unmanned aircraft, and other aerospace applications where decisions must be made in uncertain, dynamic environments while maintaining safety and efficiency. Research at SISL focuses on efficient computational methods for deriving optimal decision strategies from high-dimensional, probabilistic problem representations. He is an author of "Decision Making under Uncertainty: Theory and Application" (2015), "Algorithms for Optimization" (2019), and "Algorithms for Decision Making" (2022), all from MIT Press. He is a third generation pilot.
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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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Christoforos Kozyrakis
Professor of Electrical Engineering and of Computer Science
BioChristos Kozyrakis is a Professor of Electrical Engineering and Computer Science at Stanford University. His primary research areas are computer architecture and computer systems. His current work focuses on cloud computing, systems for machine learning, and machine learning for systems. Christos leads the MAST research group. He is also the faculty director of the Stanford Platform Lab.
Christos holds a BS degree from the University of Crete and a PhD degree from the University of California at Berkeley. He is a fellow of the ACM and the IEEE. He has received the ACM SIGARCH Maurice Wilkes Award, the ISCA Influential Paper Award, the NSF Career Award, the Okawa Foundation Research Grant, and faculty awards by IBM, Microsoft, and Google. -
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.
