School of Engineering
Showing 1,701-1,800 of 6,719 Results
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David Freyberg
Associate Professor of Civil and Environmental Engineering, Emeritus
Current Research and Scholarly InterestsMy students and I study sediment and water balances in aging reservoirs, collaborative governance of transnational fresh waters, the design of centralized and decentralized wastewater collection, treatment, and reuse systems in urban areas, and hydrologic ecosystem services in urban areas and in systems for which sediment production, transport, and deposition have significant consequences.
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Oliver Fringer
Professor of Civil and Environmental Engineering and of Oceans
BioFringer's research focuses on the development and application of numerical models and high-performance computational techniques to the study of fundamental processes that influence the dynamics of the coastal ocean, rivers, lakes, and estuaries.
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Ian Fu
Ph.D. Student in Aeronautics and Astronautics, admitted Autumn 2024
Masters Student in Aeronautics and Astronautics, admitted Spring 2026Current Research and Scholarly InterestsPlanetary Science, Ocean worlds and Icy Satellites, Space Missions, Autonomy
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Hajime Fujita
Ph.D. Student in Bioengineering, admitted Autumn 2022
Current Research and Scholarly InterestsBiosensors
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Gerald Fuller
Fletcher Jones Professor in the School of Engineering
BioThe processing of complex liquids (polymers, suspensions, emulsions, biological fluids) alters their microstructure through orientation and deformation of their constitutive elements. In the case of polymeric liquids, it is of interest to obtain in situ measurements of segmental orientation and optical methods have proven to be an excellent means of acquiring this information. Research in our laboratory has resulted in a number of techniques in optical rheometry such as high-speed polarimetry (birefringence and dichroism) and various microscopy methods (fluorescence, phase contrast, and atomic force microscopy).
The microstructure of polymeric and other complex materials also cause them to have interesting physical properties and respond to different flow conditions in unusual manners. In our laboratory, we are equipped with instruments that are able to characterize these materials such as shear rheometer, capillary break up extensional rheometer, and 2D extensional rheometer. Then, the response of these materials to different flow conditions can be visualized and analyzed in detail using high speed imaging devices at up to 2,000 frames per second.
There are numerous processes encountered in nature and industry where the deformation of fluid-fluid interfaces is of central importance. Examples from nature include deformation of the red blood cell in small capillaries, cell division and structure and composition of the tear film. Industrial applications include the processing of emulsions and foams, and the atomization of droplets in ink-jet printing. In our laboratory, fundamental research is in progress to understand the orientation and deformation of monolayers at the molecular level. These experiments employ state of the art optical methods such as polarization modulated dichroism, fluorescence microscopy, and Brewster angle microscopy to obtain in situ measurements of polymer films and small molecule amphiphile monolayers subject to flow. Langmuir troughs are used as the experimental platform so that the thermodynamic state of the monolayers can be systematically controlled. For the first time, well characterized, homogeneous surface flows have been developed, and real time measurements of molecular and microdomain orientation have been obtained. These microstructural experiments are complemented by measurements of the macroscopic, mechanical properties of the films. -
Sydney Fultz-Waters
Ph.D. Student in Materials Science and Engineering, admitted Summer 2024
Masters Student in Materials Science and Engineering, admitted Autumn 2023BioSydney is a Ph.D student in the Materials Science and Engineering department at Stanford University, co-advised by Prof. Shan X. Wang and Prof. Eric Pop. She received her B.S. in Materials Engineering from California Polytechnic State University, San Luis Obispo in 2023. Her research focuses on low dimensional magnetic materials for electronic applications.
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Vansh Vikeshkumar Gadhia
Undergraduate, Electrical Engineering
BioVansh is an undergraduate from Kenya studying Electrical Engineering and a research fellow in the Krishnan Lab. His passions involve bioelectronics, implantable devices, and the development of diagnostic tools for early detection of diseases.
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Abi Gandhi
Aerospace Prototyping Lab Manager, Aeronautics and Astronautics
Current Role at StanfordAerospace Prototyping Lab Manager, Aeronautics and Astronautics
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Swapnil Gandhi
Ph.D. Student in Computer Science, admitted Autumn 2022
BioMy broad research interests include distributed systems and cloud computing – in particular, I am interested in the system-side problems associated with learning, deploying, and operationalizing machine learning models at scale.
Previously, I was a Research Fellow at Microsoft Research India and prior to that obtained my Masters (by Research) in Computer and Data Systems from the Indian Institute of Science (IISc). -
Surya Ganguli
Associate Professor of Applied Physics, Senior Fellow at the Stanford Institute for Human-Centered AI and Associate Professor, by courtesy, of Neurobiology and of Electrical Engineering
Current Research and Scholarly InterestsTheoretical / computational neuroscience
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Andrew Kean Gao
Masters Student in Computer Science, admitted Autumn 2023
BioImmersed in the AI space since 2019, Andrew is excited by the potential of AI/ML in all domains of industry, academia, and life. He has built several popular projects in AI, such as Lightspeed Multithreading and BibleGPT. His team won a Grand Prize at Stanford TreeHacks 2023 out of nearly 2,000 competitors. Beyond AI, Andrew has conducted research in molecular biology, disease diagnosis, drug design, and computational immunology.
Software developer and student at Stanford University specializing in artificial intelligence and large language models.
Personal websites:
https://andrew.md/
https://andrewgao.dev/ -
Chongkai Gao
Graduate Visiting Researcher Student, Computer Science
BioChongkai is a PhD student from the National University of Singapore, and a visiting student researcher at Stanford University in Prof. Fei-Fei Li's group. His research is about building hierarchical foundation models and structured evaluation of general-purpose robot manipulation. Homepage: https://chongkaigao.com/.
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Grace Gao
Associate Professor of Aeronautics and Astronautics and, by courtesy, of Electrical Engineering
BioGrace Gao is an associate professor in the Department of Aeronautics and Astronautics at Stanford University, with a courtesy appointment in the Electrical Engineering Department. She leads the Navigation and Autonomous Vehicles Laboratory (NAV Lab) and serves as co-director of the Stanford AI Safety Center and co-lead of the Stanford SystemX Robotics area. Her research focuses on robust and secure perception, localization, and navigation, with applications in crewed and uncrewed aerial vehicles, autonomous cars, humanoid robots, and space robotics.
Prof. Gao has won numerous awards, including the NSF CAREER Award, the Institute of Navigation Early Achievement Award, the RTCA William E. Jackson Award, and the Inspiring Early Academic Career Award from Stanford University. In addition to her research achievements, she has received significant recognition for her teaching and advising, including the AIAA Stanford Chapter Excellence in Advising Award and the Excellence in Teaching Award. -
Jiechao Gao
Postdoctoral Scholar, Civil and Environmental Engineering
BioJiechao Gao is a Postdoctoral Research Associate at Stanford University's Center for Sustainable Development and Global Competitiveness. He received his Ph.D. in Computer Science from the University of Virginia, his M.S. in Electrical Engineering from Columbia University, and dual B.S. degrees in Applied Physics and Financial Engineering from Jilin University. Prior to joining Stanford, he served as an Associate Research Scientist at Columbia University.
His research spans federated learning, large language model (LLM) interpretability and efficiency, reinforcement learning, and privacy-preserving AI, with applications in healthcare, smart buildings, IoV, and finance. He has published extensively at top venues including ICLR, NeurIPS, ICML, AAAI, EMNLP, KDD, CVPR, ACL, etc. He serves as Area Chair or Senior Program Committee member for conferences such as ICLR, NeurIPS, ICML, AAAI, EMNLP, KDD, IJCAI, IJCNN, ICASSP, and reviews for journals such as JMLR, IEEE IoT-J, and IEEE TITS. His recognitions include the Google HE Faculty AI Fellowship (2026), Stanford/Elsevier Global Top 2% Scientists (2024 & 2025), and multiple Best Paper Nominations. -
Xiaojing Gao
Assistant Professor of Chemical Engineering
Current Research and Scholarly InterestsHow do we design biological systems as “smart medicine” that sense patients’ states, process the information, and respond accordingly? To realize this vision, we will tackle fundamental challenges across different levels of complexity, such as (1) protein components that minimize their crosstalk with human cells and immunogenicity, (2) biomolecular circuits that function robustly in different cells and are easy to deliver, (3) multicellular consortia that communicate through scalable channels, and (4) therapeutic modules that interface with physiological inputs/outputs. Our engineering targets include biomolecules, molecular circuits, viruses, and cells, and our approach combines quantitative experimental analysis with computational simulation. The molecular tools we build will be applied to diverse fields such as neurobiology and cancer therapy.
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Lorenza Garau Paganella
Postdoctoral Scholar, Mechanical Engineering
BioLorenza was born in Italy in 1997 and is currently a postdoctoral fellow at Stanford University with Prof. Chaudhuri, supported by an SNSF fellowship. Her research focuses on engineering biomaterials to investigate cell–extracellular matrix interactions and mechanotransduction in 2D and 3D cell cultures, aiming to advance biomedical understanding of tissue remodeling and disease.
Lorenza obtained her PhD (2024) in Mechanical and Process Engineering from ETH Zurich, where she developed hydrogel scaffolds and protocols for protein isolation to study cell behavior in engineered microenvironments.
Before her PhD, Lorenza completed her MSc at ETH Zurich and BSc at University of Trieste in Process Engineering, graduating both cum laude. During this time her focus was on biomaterials for drug delivery which she complemented with an internship in Roche. She has worked in interdisciplinary teams combining engineering and biology and is motivated by research that bridges fundamental science with clinical impact. -
Harold Gardon
Masters Student in Aeronautics and Astronautics, admitted Autumn 2025
BioFrench student specializing in mechanical engineering. Passionate about basketball and aerospace, I am pursuing a Master of Science in Aeronautics and Astronautics and hope to specialize in rocket propulsion.
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Raul Garreta Tompson
Graduate, Stanford Center for Professional Development
BioI'm a tech entrepreneur, passionate about Artificial Intelligence (AI), with extensive experience in Machine Learning, Natural Language Processing and Robotics.
I started in Machine Learning back in 2005, building an artificial Go player with Neural Networks and Reinforcement Learning. That was ten years before AlphaGo used the same principles :)
Then worked on a bunch of companies including programming video games and implementing firmware for implantable medical devices.
In 2007 I started lecturing Machine Learning and NLP as a professor at the Computer Science Institute of UDELAR for 9 years.
In 2009 I co-founded Tryolabs, Python dev shop specialized in building products with AI.
In 2013 I co-authored with PhD Guillermo Moncecchi a technical book about an introduction to applied Machine Learning with Python programming language.
In 2014 I founded and led MonkeyLearn to make Machine Learning and NLP accessible to all companies and users. I raised a total of $4.2m from top tier Venture Capital and angel investors in Silicon Valley. I led all R&D and business operations, selling our product to top companies in the US.
In 2020 I finished my master thesis in Artificial Intelligence, "Data Efficient Deep Learning Models for Text Classification", where I compared multiple state of the art models, including language models.
In 2022 I exited MonkeyLearn to Medallia and joined as Sr Director leading AI research and development.
I'm an active investor, I invest in public markets but also in private companies, particularly tech startups and software product companies. I'm also LP in two venture capital funds, Uncork Capital and Garuda Ventures.
Currently researching and building on Artificial Intelligence for Robotics. -
Matthias Garten
Assistant Professor of Microbiology and Immunology and of Bioengineering
Current Research and Scholarly InterestsWith a creative, collaborative, biophysical mindset, we aim to understand the ability non-model organisms to interface with environment to a point at which we can exploit the mechanisms finding cures against diseases and use the mechanisms as tools that we can use to engineer the environment. By developing approaches that allow a quantitative understanding and manipulation of molecular transport our research makes non-model organisms accessible to researchers and engineers.
Specifically, we are studying how the malaria parasite takes control over red blood cells. By learning the biophysical principles of transport in between the host and the parasite we can design ways to kill the parasite or exploit it to reengineer red blood cells. The transport we study is broadly encompassing everything from ions to lipids and proteins. We use variations of quantitative microscopy and electrophysiology to gain insight into the unique strategies the parasite evolved to survive. -
Aimee Garza
Faculty Administrator, Computer Science
Current Role at StanfordCS DEI Program Coordinator
