School of Engineering
Showing 2,351-2,400 of 6,587 Results
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Fabio Hübel
Graduate Visiting Researcher Student, Aeronautics and Astronautics
BioVisiting Student Research at Marco Pavone's Group (Autonomous Systems Lab).
Master Thesis in autonomous navigation and exploration for quadrupeds. -
Robert Huggins
Professor of Materials Science and Engineering, Emeritus
BioProfessor Huggins joined Stanford as Assistant Professor in 1954, was promoted to Associate Professor in 1958, and to Professor in 1962.
His research activities have included studies of imperfections in crystals, solid-state reaction kinetics, ferromagnetism, mechanical behavior of solids, crystal growth, and a wide variety of topics in physical metallurgy, ceramics, solid state chemistry and electrochemistry. Primary attention has recently been focused on the development of understanding of solid state ionic phenomena involving solid electrolytes and mixed ionic-electronic conducting materials containing atomic or ionic species such as lithium, sodium or oxygen with unusually high mobility, as well as their use in novel battery and fuel cell systems, electrochromic optical devices, sensors, and in enhanced heterogeneous catalysis. He was also involved in the development of the understanding of the key role played by the phase composition and oxygen stoichiometry in determining the properties of high temperature oxide superconductors.
Topics of particular recent interest have been related to energy conversion and storage, including hydrogen transport and hydride formation in metals, alloys and intermetallic compounds, and various aspects of materials and phenomena related to advanced lithium batteries.
He has over 400 professional publications, including three books; "Advanced Batteries", published by Springer in 2009, "Energy Storage", published by Springer in 2010, and Energy Storage, Second Edition in 2016. -
Alissa Hummer
Postdoctoral Scholar, Bioengineering
BioAlissa is a Schmidt Science Fellow in the labs of Emma Lundberg and Wah Chiu. She is integrating microscopy techniques with AI to study and model cellular processes. Prior to her postdoc, Alissa completed her PhD at the University of Oxford, where she developed machine learning models for therapeutic antibody optimization and design.
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Kuo-Han Hung
Masters Student in Computer Science, admitted Autumn 2025
BioFirst-year Computer Science Master’s student at Stanford, originally from Taipei, Taiwan.
Passionate about robotics and AI, with a focus on developing robot policies that are more generalizable and reliable. Open to research collaborations and work opportunities in embodied AI and machine learning.
Website: https://khhung-906.github.io -
Sydney Hunt
Ph.D. Student in Electrical Engineering, admitted Autumn 2023
BioSydney Hunt (she/her), from Cornwall, New York, is a Knight-Hennessy Scholar pursuing a PhD in electrical engineering with a focus on brain-computer interfaces (BCI) at Stanford School of Engineering. She is advised by Paul Nuyujukian, MD, PhD in the Brain Interfacing Laboratory.
She currently serves as a Trustee on the Duke University Board of Trustees, Knight-Hennessy Scholar Ambassador, and on the Knight-Hennessy Scholar Experience Committee. She graduated with distinction from Duke University with bachelor’s degrees in electrical/computer engineering and computer science (concentration in artificial intelligence and machine learning), and a minor in gender, sexuality, and feminist studies.
An aspiring professor, Sydney passionately commits herself to STEM retention as a founding member of both the nonprofit CS Sidekicks and Duke’s S.P.I.R.E. Fellows Living Learning Community. She conducted and published her BCI research at Caltech (Richard Andersen’s lab) and MIT (Polina Anikeeva’s lab) through the WAVE Fellows and MIT SRP-Bio programs, respectively. She enjoys playing soccer, trying new food, and dad jokes. Sydney is certified in Mental Health First Aid and a recipient of Duke’s Reginaldo Howard Memorial Scholarship. -
Hillard Huntington
Executive Director, Energy Modeling Forum
Researcher, Management Science and Engineering - Energy Modeling Forum
Staff, Management Science and Engineering - Energy Modeling ForumBioHuntington is Executive Director of Stanford University's Energy Modeling Forum, where he conducts studies to improve the usefulness of models for understanding energy and environmental problems. In 2005 the Forum received the prestigious Adelman-Frankel Award from the International Association for Energy Economics for its "unique and innovative contribution to the field of energy economics."
His current research interests are modeling energy security, energy price shocks, energy market impacts of environmental policies, and international natural gas and LNG markets. In 2002 he won the Best Paper Award from the Energy Journal for a paper co-authored with Professor Dermot Gately of New York University.
He is a Senior Fellow and a past-President of the United States Association for Energy Economics and a member of the National Petroleum Council. He was also Vice-President for Publications for the International Association for Energy Economics and a member of the American Statistical Association's Committee on Energy Data. Previously, he served on a joint USA-Russian National Academy of Sciences Panel on energy conservation research and development.
Huntington has testified before the U.S. Senate Committee on Foreign Relations and the California Energy Commission.
Prior to coming to Stanford in 1980, he held positions in the corporate and government sectors with Data Resources Inc., the U.S. Federal Energy Administration, and the Public Utilities Authority in Monrovia, Liberia (as a U.S. Peace Corps Volunteer). -
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.
