School of Engineering
Showing 161-180 of 396 Results
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Jikai Jin
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2023
BioI am currently a Ph.D. student of the The Institute for Computational and Mathematical Engineering (ICME) at Stanford university. Prior to joining Stanford, I obtained my bachelor degree in computational mathematics at the School of Mathematical Sciences, Peking University, fortunately having Prof. Liwei Wang as my research advisor. My research is highly interdisciplinary across machine learning, statistics, operations research. While primarily focusing on theoretical aspects, the ultimate goal of my research is to develop state-of-the-art solutions for important real-world problems.
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Ramesh Johari
Professor of Management Science and Engineering, Senior Fellow at the Stanford Institute for Human-Centered Artificial Intelligence (HAI) and, by courtesy, of Electrical Engineering
BioJohari is broadly interested in the design, economic analysis, and operation of online platforms, as well as statistical and machine learning techniques used by these platforms (such as search, recommendation, matching, and pricing algorithms).
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Riley Juenemann
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2021
BioThird-year Computational and Mathematical Engineering (ICME) PhD Candidate @ Stanford University passionate about research at the intersection of mathematics, computing, and biology.
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Joseph Kahn
Harald Trap Friis Professor
BioJoseph M. Kahn is a Professor of Electrical Engineering at Stanford University. His research addresses communication and imaging through optical fibers, including modulation, detection, signal processing and spatial multiplexing. He received A.B. and Ph.D. degrees in Physics from U.C. Berkeley in 1981 and 1986. From 1987-1990, he was at AT&T Bell Laboratories, Crawford Hill Laboratory, in Holmdel, NJ. He was on the Electrical Engineering faculty at U.C. Berkeley from 1990-2003. In 2000, he co-founded StrataLight Communications, which was acquired by Opnext, Inc. in 2009. He received the National Science Foundation Presidential Young Investigator Award in 1991 and is a Life Fellow of the IEEE.
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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. -
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.
