School of Engineering
Showing 1-100 of 192 Results
-
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.
-
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.
-
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
-
Charbel Farhat
Vivian Church Hoff Professor of Aircraft Structures and Professor of Aeronautics and Astronautics
Current 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.
-
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.
-
Shaghayegh Fazliani
Ph.D. Student in Mathematics, admitted Autumn 2021
Grader EE 261, Electrical Engineering - Student ServicesBioShaghayegh, my first name, means red poppy in Persian. Here in the US, I go with 'Shay' as a nickname since Shaghayegh might be hard to pronounce! I graduated with a bachelor's degree in mathematics from Sharif University of Technology, focusing on pure mathematics. As of September 2021, I'll be a mathematics graduate student at Stanford University.
-
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.
-
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.
-
Jeffrey A. Feinstein, MD, MPH
Dunlevie Family Professor of Pulmonary Vascular Disease and Professor, by courtesy, of Bioengineering
Current 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.
-
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 Mechanical Engineering, admitted Spring 2024BioMS/PhD Student and Hypersonics Researcher in the High-Temperature Gasdynamics Laboratory (Hanson group).
-
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).
-
Chelsea Finn
Assistant Professor of Computer Science and of Electrical Engineering
BioChelsea Finn is an Assistant Professor in Computer Science and Electrical Engineering at Stanford University, and the William George and Ida Mary Hoover Faculty Fellow. Professor Finn's research interests lie in the ability to enable robots and other agents to develop broadly intelligent behavior through learning and interaction. Her work lies at the intersection of machine learning and robotic control, including topics such as end-to-end learning of visual perception and robotic manipulation skills, deep reinforcement learning of general skills from autonomously collected experience, and meta-learning algorithms that can enable fast learning of new concepts and behaviors. Professor Finn received her Bachelors degree in Electrical Engineering and Computer Science at MIT and her PhD in Computer Science at UC Berkeley. Her research has been recognized through the ACM doctoral dissertation award, an NSF graduate fellowship, a Facebook fellowship, the C.V. Ramamoorthy Distinguished Research Award, and the MIT Technology Review 35 under 35 Award, and her work has been covered by various media outlets, including the New York Times, Wired, and Bloomberg. Throughout her career, she has sought to increase the representation of underrepresented minorities within CS and AI by developing an AI outreach camp at Berkeley for underprivileged high school students, a mentoring program for underrepresented undergraduates across three universities, and leading efforts within the WiML and Berkeley WiCSE communities of women researchers.
Website: https://ai.stanford.edu/~cbfinn -
Michael Fischbach
Liu (Liao) Family Professor
Current Research and Scholarly InterestsThe microbiome carries out extraordinary feats of biology: it produces hundreds of molecules, many of which impact host physiology; modulates immune function potently and specifically; self-organizes biogeographically; and exhibits profound stability in the face of perturbations. Our lab studies the mechanisms of microbiome-host interactions. Our approach is based on two technologies we recently developed: a complex (119-member) defined gut community that serves as an analytically manageable but biologically relevant system for experimentation, and new genetic systems for common species from the microbiome. Using these systems, we investigate mechanisms at the community level and the strain level.
1) Community-level mechanisms. A typical gut microbiome consists of 200-250 bacterial species that span >6 orders of magnitude in relative abundance. As a system, these bacteria carry out extraordinary feats of metabolite consumption and production, elicit a variety of specific immune cell populations, self-organize geographically and metabolically, and exhibit profound resilience against a wide range of perturbations. Yet remarkably little is known about how the community functions as a system. We are exploring this by asking two broad questions: How do groups of organisms work together to influence immune function? What are the mechanisms that govern metabolism and ecology at the 100+ strain scale? Our goal is to learn rules that will enable us to design communities that solve specific therapeutic problems.
2) Strain-level mechanisms. Even though gut and skin colonists live in communities, individual strains can have an extraordinary impact on host biology. We focus on two broad (and partially overlapping) categories:
Immune modulation: Can we redirect colonist-specific T cells against an antigen of interest by expressing it on the surface of a bacterium? How do skin colonists induce high levels of Staphylococcus-specific antibodies in mice and humans?
Abundant microbiome-derived molecules: By constructing single-strain/single-gene knockouts in a complex defined community, we will ask: What are the effects of bacterially produced molecules on host metabolism and immunology? Can the molecular output of low-abundance organisms impact host physiology?
3) Cell and gene therapy. We have begun two new efforts in mammalian cell and gene therapies. First, we are developing methods that enable cell-type specific delivery of genome editing payloads in vivo. We are especially interested in delivery vehicles that are customizable and easy to manufacture. Second, we have begun a comprehensive genome mining effort with an emphasis on understudied or entirely novel enzyme systems with utility in mammalian genome editing. -
Martin Fischer
Kumagai Professor in the School of Engineering
BioProfessor Fischer's research goals are to improve the productivity of project teams involved in designing, building, and operating facilities and to enhance the sustainability of the built environment. His work develops the theoretical foundations and applications for virtual design and construction (VDC). VDC methods support the design of a facility and its delivery process and help reduce the costs and maximize the value over its lifecycle. His research has been used by many small and large industrial government organizations around the world.
-
Ian Fisher
Professor of Applied Physics and, by courtesy, of Materials Science and Engineering
Current Research and Scholarly InterestsOur research focuses on the study of quantum materials with unconventional magnetic & electronic ground states & phase transitions. Emphasis on design and discovery of new materials. Recent focus on use of strain as a probe of, and tuning parameter for, a variety of electronic states. Interests include unconventional superconductivity, quantum phase transitions, nematicity, multipolar order, instabilities of low-dimensional materials and quantum magnetism.
