School of Engineering
Showing 151-200 of 444 Results
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Grace Hawthorne
Adjunct Professor, d.school
BioGrace Hawthorne is an entrepreneur, artist, author and educator. She is the Founder/CEO of Paper Punk, an award-winning Origami-meets-LEGO mashup that helps people exercise their creativity, and Foldmade, an innovative work supply system that helps people get stuff done. As an Adjunct Professor at Stanford University's design institute (aka: the d.school) since 2008, she has taught courses on creativity and failure for over fifteen years and spearheaded a groundbreaking research project on creative capacity building published in Science and covered by Wired magazine. Previously, she founded ReadyMade, the culturally disruptive design magazine that ignited the maker movement, and led its acquisition by Meredith Corporation (NASDAQ: MDP) and co-authored the critically acclaimed book on reuse design, ReadyMade: How to Make (Almost) Everything (Random House/Potter). Her products can be found on the shelves of mass retailers and her artwork has been exhibited in several national museums including the Smithsonian Cooper-Hewitt Design Museum Triennial and her products can be found at mass retailers nationwide. She holds an MBA from the Anderson School at UCLA, MFA from UCLA’s School of Film and Television, and a BA in Visual Communication from UC Berkeley. Her newest book titled, Make Possibilities Happen: How to Transform Ideas into Reality (Random House/10Speed) is part of Stanford d.school’s ten design guides. Grace has dedicated her life to making things and experiences that cultivate human creativity through the marriage of art + commerce. She believes that (almost) anything is possible. www.graciemade.com
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Mark Horowitz
Fortinet Founders Chair of the Department of Electrical Engineering, Yahoo! Founders Professor in the School of Engineering, Professor of Computer Science, and Senior Fellow at the Hoover Institution
BioProfessor Horowitz initially focused on designing high-performance digital systems by combining work in computer-aided design tools, circuit design, and system architecture. During this time, he built a number of early RISC microprocessors, and contributed to the design of early distributed shared memory multiprocessors. In 1990, Dr. Horowitz took leave from Stanford to help start Rambus Inc., a company designing high-bandwidth memory interface technology. After returning in 1991, his research group pioneered many innovations in high-speed link design, and many of today’s high speed link designs are designed by his former students or colleagues from Rambus.
In the 2000s he started a long collaboration with Prof. Levoy on computational photography, which included work that led to the Lytro camera, whose photographs could be refocused after they were captured.. Dr. Horowitz's current research interests are quite broad and span using EE and CS analysis methods to problems in neuro and molecular biology to creating new agile design methodologies for analog and digital VLSI circuits. He remains interested in learning new things, and building interdisciplinary teams. -
Gianluca Iaccarino
Robert Bosch Chair of the Department of Mechanical Engineering and Joseph L. and Roberta M. Rodgers Professor
Current Research and Scholarly InterestsComputing and data for energy, health and engineering
Challenges in energy sciences, green technology, transportation, and in general, engineering design and prototyping are routinely tackled using numerical simulations and physical testing. Computations barely feasible two decades ago on the largest available supercomputers, have now become routine using turnkey commercial software running on a laptop. Demands on the analysis of new engineering systems are becoming more complex and multidisciplinary in nature, but exascale-ready computers are on the horizon. What will be the next frontier? Can we channel this enormous power into an increased ability to simulate and, ultimately, to predict, design and control? In my opinion two roadblocks loom ahead: the development of credible models for increasingly complex multi-disciplinary engineering applications and the design of algorithms and computational strategies to cope with real-world uncertainty.
My research objective is to pursue concerted innovations in physical modeling, numerical analysis, data fusion, probabilistic methods, optimization and scientific computing to fundamentally change our present approach to engineering simulations relevant to broad areas of fluid mechanics, transport phenomena and energy systems. The key realization is that computational engineering has largely ignored natural variability, lack of knowledge and randomness, targeting an idealized deterministic world. Embracing stochastic scientific computing and data/algorithms fusion will enable us to minimize the impact of uncertainties by designing control and optimization strategies that are robust and adaptive. This goal can only be accomplished by developing innovative computational algorithms and new, physics-based models that explicitly represent the effect of limited knowledge on the quantity of interest.
Multidisciplinary Teaching
I consider the classical boundaries between disciplines outdated and counterproductive in seeking innovative solutions to real-world problems. The design of wind turbines, biomedical devices, jet engines, electronic units, and almost every other engineering system requires the analysis of their flow, thermal, and structural characteristics to ensure optimal performance and safety. The continuing growth of computer power and the emergence of general-purpose engineering software has fostered the use of computational analysis as a complement to experimental testing in multiphysics settings. Virtual prototyping is a staple of modern engineering practice! I have designed a new undergraduate course as an introduction to Computational Engineering, covering theory and practice across multidisciplanary applications. The emphasis is on geometry modeling, mesh generation, solution strategy and post-processing for diverse applications. Using classical flow/thermal/structural problems, the course develops the essential concepts of Verification and Validation for engineering simulations, providing the basis for assessing the accuracy of the results. -
Alexander Ioannidis
Assistant Professor (Research) of Genetics and of Biomedical Data Science
Adjunct Professor, Institute for Computational and Mathematical Engineering (ICME)BioDr. Ioannidis earned his Ph.D. from Stanford University in Computational and Mathematical Engineering together with an M.S. in Management Science and Engineering (Optimization).
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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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Antony Jameson
Professor (Research) of Aeronautics and Astronautics, Emeritus
BioProfessor Jameson's research focuses on the numerical solution of partial differential equations with applications to subsonic, transonic, and supersonic flow past complex configurations, as well as aerodynamic shape optimization.
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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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Ronald "Ronny" Junkins
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2026
BioI'm an incoming PhD student at Stanford at the Institute of Computational and Mathematical Engineering (ICME). Before that, also at Stanford, I completed my master's degree in computer science and my bachelor's degree in mathematics.
Broadly, I am interested in deep learning theory, including developing interpretable machine learning models and mathematics which helps explain their behavior. Currently, I am also interested in problems in tabular data. If you are interested in collaborating, please feel free to reach out! -
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.
