Stanford University
Showing 1-100 of 207 Results
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Roya Firoozi
Postdoctoral Scholar, Aeronautics and Astronautics
BioRoya is currently a postdoctoral researcher at Stanford University, Multi-Robot Systems Laboratory. She received her bachelor's degree in mechanical engineering and her Ph.D. in control theory, with minors in optimization and machine learning from the University of California, Berkeley. Her research focuses on enabling safe robot autonomy powered by generative AI in interactive, open-world environments. Roya has received the NSF Postdoctoral Fellowship Award, the UC Berkeley Outstanding Graduate Student Instructor Award, and the UC Berkeley Chancellor’s Award. She was recognized as a rising star in EECS and Aerospace Engineering. Outside of her research, she has served as the robotics mentor at Stanford AI4ALL outreach program that aims to increase diversity in artificial intelligence.
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Chaofei Fan
Ph.D. Student in Computer Science, admitted Autumn 2020
BioI’m a Ph.D. student at Stanford unraveling the future of brain-computer interfaces to revolutionize communication.
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Jonathan Fan
Associate Professor of Electrical Engineering
Current Research and Scholarly InterestsOptical engineering plays a major role in imaging, communications, energy harvesting, and quantum technologies. We are exploring the next frontier of optical engineering on three fronts. The first is new materials development in the growth of crystalline plasmonic materials and assembly of nanomaterials. The second is novel methods for nanofabrication. The third is new inverse design concepts based on optimization and machine learning.
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Qingyuan Fan
Ph.D. Student in Materials Science and Engineering, admitted Autumn 2019
BioPh.D Student, Dept. of Materials Science and Engineering, Stanford 09.2019 - present
Undergraduate, Zhejiang University 2015-2019
Visiting Student Researcher, Aaron Lindenberg's group, Dept. of Materials Science and Engineering, Stanford 07.2018-09.2018 -
Shanhui Fan
Joseph and Hon Mai Goodman Professor of the School of Engineering and Professor, by courtesy, of Applied Physics
BioFan's research interests are in fundamental studies of nanophotonic structures, especially photonic crystals and meta-materials, and applications of these structures in energy and information technology applications
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Saman Farhangdoust
Postdoctoral Scholar, Aeronautics and Astronautics
BioDr. Saman Farhangdoust is pursuing the goal of using his interdisciplinary knowledge to advance the Smart City and Space concept and make a lasting impact on society. He enjoys venturing into new disciplines to combine cutting-edge technologies and develop novel solutions to today’s structural safety problems.
As a Postdoctoral Scholar at Stanford University, Saman works on multi-functional materials and smart structures with particular emphases on intelligent self-sensing diagnostics and integrated health management for space and aircraft structures.
Outside of his research at Stanford, Saman is collaborating with MIT Media Lab as a Technical Consultant and also with Boeing Research and Technology as a Research Consultant to advance sensing and structural health monitoring systems.
Saman is considered a talented young researcher who has made valuable multidisciplinary contributions at an international level. These research activities have led to more than 40 publications including journal articles, conference proceedings, a textbook, U.S. Patents, national reports and guidelines to date. -
Charbel Farhat
Vivian Church Hoff Professor of Aircraft Structures and Professor of Aeronautics and Astronautics
On Partial Leave from 04/01/2024 To 06/30/2024Current Research and Scholarly InterestsCharbel Farhat and his Research Group (FRG) develop mathematical models, advanced computational algorithms, and high-performance software for the design, analysis, and digital twinning of complex systems in aerospace, marine, mechanical, and naval engineering. They contribute major advances to Simulation-Based Engineering Science. Current engineering foci in research are on reliable autonomous carrier landing in rough seas; dissipation of vertical landing energies through structural flexibility; nonlinear aeroelasticity of N+3 aircraft with High Aspect Ratio (HAR) wings; pulsation and flutter of a parachute; pendulum motion in main parachute clusters; coupled fluid-structure interaction (FSI) in supersonic inflatable aerodynamic decelerators for Mars landing; flight dynamics of hypersonic systems and their trajectories; and advanced digital twinning. Current theoretical and computational emphases in research are on high-performance, multi-scale modeling for the high-fidelity analysis of multi-component, multi-physics problems; discrete-event-free embedded boundary methods for CFD and FSI; efficient Bayesian optimization using physics-based surrogate models; modeling and quantifying model-form uncertainty; probabilistic, physics-based machine learning; mechanics-informed artificial neural networks for data-driven constitutive modeling; and efficient nonlinear projection-based model order reduction for time-critical applications such as design, active control, and digital twinning.
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Humera Fasihuddin
d.school Systems Architect, d.school
BioHumera co-directs the University Innovation Fellows Program. She trains students to create lasting institutional impact that enhances the innovation and entrepreneurship ecosystem on campus.
Prior to the University Innovation Fellows program, she worked for nonprofit VentureWell and led the creation of numerous programs including the organization’s first foray in advanced venture training workshops, which today account for over half of the 501c(3)’s income. Before that, she created innovation networks between industry and the University of Massachusetts Amherst under an NSF Partnership for Innovation grant.
Humera began her career at the publicly-traded UK firm Rexam, serving as product manager in their precision coated materials subsidiary. Humera holds an M.B.A. from UMass Amherst and a B.S. from Smith College. -
Kayvon Fatahalian
Associate Professor of Computer Science
BioKayvon Fatahalian is an Associate Professor in the Computer Science Department at Stanford University. Kayvon's research focuses on the design of systems for real-time graphics, high-efficiency simulation engines for applications in entertainment and AI, and platforms for the analysis of images and videos at scale.
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Ron Fedkiw
Canon Professor in the School of Engineering
BioFedkiw's research is focused on the design of new computational algorithms for a variety of applications including computational fluid dynamics, computer graphics, and biomechanics.
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Vivian Feig
Assistant Professor of Mechanical Engineering
BioDr. Vivian Feig is an incoming Assistant Professor in the Mechanical Engineering department, beginning March 2024. The Feig lab aims to develop low-cost, noninvasive, and widely-accessible medical technologies that integrate seamlessly with the human body. We accomplish this by developing functional materials and devices with dynamic mechanical properties, leveraging chemistry and physics insights to engineer novel systems at multiple length scales. In pursuit of our goals, we maintain a strong emphasis on integrity and diversity, while nurturing the intellectual curiosity and holistic growth of our team members as researchers, communicators, and leaders.
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Jeffrey A. Feinstein, MD, MPH
Dunlevie Family Professor of Pulmonary Vascular Disease and Professor, by courtesy, of Bioengineering
On Partial Leave from 04/30/2024 To 05/31/2024Current Research and Scholarly InterestsResearch interests include (1) computer simulation and modeling of cardiovascular physiology with specific attention paid to congenital heart disease and its treatment, (2) the evaluation and treatment of pulmonary hypertension/pulmonary vascular diseases, and (3) development and testing of medical devices/therapies for the treatment of congenital heart disease and pulmonary vascular diseases.
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Bruno Felisberto Martins Ribeiro
Visiting Associate Professor, Computer Science
BioBruno Ribeiro is an Associate Professor in the Department of Computer Science at Purdue University and currently a Visiting Associate Professor at Stanford University. Before joining Purdue, he earned his Ph.D. from the University of Massachusetts Amherst and was a postdoctoral fellow at Carnegie Mellon University. Ribeiro has made significant contributions in the intersection between invariant theory, graph learning, and out-of-distribution robustness. Ribeiro received an NSF CAREER award in 2020, an Amazon Research Award in 2022, and multiple best paper awards.
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Steven Feng
Ph.D. Student in Computer Science, admitted Autumn 2022
BioI'm a Stanford Computer Science PhD student and NSERC PGS-D scholar, working with the Stanford AI Lab and Stanford NLP Group. I am co-advised by Michael C. Frank and Noah Goodman as part of the Language & Cognition (LangCog) and Computation & Cognition (CoCo) Labs. I am grateful to receive support from Amazon Science, Microsoft AFMR, and StabilityAI.
My ultimate goal is to blend knowledge from multiple disciplines to advance AI research. My current research centers around aligning foundation model and human learning and capabilities, particularly in reasoning, generalization, and efficiency. I have explored ways to improve the controllability of language and visual generation models, and integrate structured and multimodal information to enhance their reasoning capabilities.
I'm investigating psychologically and cognitively inspired methods for continual learning, self-improvement, and advanced reasoning in foundation models. I'm also exploring methods to bridge the data efficiency gap between human and model learning while shedding further light on human cognitive models and our efficient language and vision acquisition capabilities.
Previously, I was a master's student at Carnegie Mellon University (CMU), where I worked with Eduard Hovy and Malihe Alikhani on language generation, data augmentation, and commonsense reasoning. Before that, I was an undergraduate student at the University of Waterloo, where I worked with Jesse Hoey on dialogue agents and text generation.
My research contributions have been recognized with several publications at major conferences and a best paper award at INLG 2021. I am also an Honorable Mention for the Jessie W.H. Zou Memorial Award and CRA Outstanding Undergraduate Researcher Award.
I am a co-instructor for the Stanford CS25 Transformers course, and mentor and advise several students. I also led the organization of CtrlGen, a controllable generation workshop at NeurIPS 2021, and was involved in the GEM benchmark and workshop for NLG evaluation.
In my free time, I enjoy gaming, playing the piano and guitar, martial arts, and table tennis. I am also the founder and president of the Stanford Piano Society. -
Michele Ferretti
Ph.D. Student in Mechanical Engineering, admitted Winter 2024
Masters Student in Aeronautics and Astronautics, admitted Autumn 2023
Masters Student in Mechanical Engineering, admitted Spring 2024BioMS/PhD Student and Hypersonics Researcher in the High-Temperature Gasdynamics Laboratory (Hanson group).
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Richard Fikes
Professor (Research) of Computer Science, Emeritus
BioRichard Fikes has a long and distinguished record as an innovative leader in the development of techniques for effectively representing and using knowledge in computer systems. He is best known as co-developer of the STRIPS automatic planning system, KIF (Knowledge Interchange Format), the Ontolingua ontology representation language and Web-based ontology development environment, the OKBC (Open Knowledge Base Connectivity) API for knowledge servers, and IntelliCorp's KEE system. At Stanford, he led projects focused on developing large-scale distributed repositories of computer-interpretable knowledge, collaborative development of multi-use ontologies, enabling technology for the Semantic Web, reasoning methods applicable to large-scale knowledge bases, and knowledge-based technology for intelligence analysts. He was principal investigator of major projects for multiple Federal Government agencies including the Defense Advanced Research Projects Agency (DARPA) and the Intelligence Community’s Advanced Research and Development Activity (ARDA).
