School of Engineering
Showing 21-40 of 52 Results
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Michael Lepech
Professor of Civil and Environmental Engineering and Senior Fellow at the Woods Institute for the Environment
BioUnsustainable energy and material consumption, waste production, and emissions are some of today’s most pressing global concerns. To address these concerns, civil engineers are now designing facilities that, for example, passively generate power, reuse waste, and are carbon neutral. These designs are based foremost on longstanding engineering theory. Yet woven within this basic knowledge must be new science and new technologies, which advance the field of civil engineering to the forefront of sustainability-focused design.
My research develops fundamental engineering design concepts, models, and tools that are tightly integrated with quantitative sustainability assessment and service life modeling across length scales, from material scales to system scales, and throughout the early design, project engineering, construction, and operation life cycle phases of constructed facilities. My research follows the Sustainable Integrated Materials, Structures, Systems (SIMSS) framework. SIMSS is a tool to guide the multi-scale design of sustainable built environments, including multi-physics modeling informed by infrastructure sensing data and computational learning and feedback algorithms to support advanced digital-twinning of engineered systems. Thus, my research applies SIMMS through two complementary research thrusts; (1) developing high-fidelity quantitative sustainability assessment methods that enable civil engineers to quickly and probabilistically measure sustainability indicators, and (2) creating multi-scale, fundamental engineering tools that integrate with sustainability assessment and facilitate setting and meeting sustainability targets throughout the life cycle of constructed facilities.
Most recently, my research forms the foundation of the newly created Stanford Center at the Incheon Global Campus (SCIGC) in South Korea, a university-wide research center examining the potential for smart city technologies to enhance the sustainability of urban areas. Located in the smart city of Songdo, Incheon, South Korea, SCIGC is a unique global platform to (i) advance research on the multi-scale design, construction, and operation of sustainable built environments, (ii) demonstrate to cities worldwide the scalable opportunities for new urban technologies (e.g., dense urban sensing networks, dynamic traffic management, autonomous vehicles), and (iii) improve the sustainability and innovative capacity of increasingly smarter cities globally.
With an engineering background in civil and environmental engineering and material science (BSE, MSE, PhD), and business training in strategy and finance (MBA), I continue to explore to the intersection of entrepreneurship education, innovation capital training, and the potential of startups to more rapidly transfer and scale technologies to solve some of the world's most challenging problems. -
Jure Leskovec
Professor of Computer Science
BioJure Leskovec is Professor of Computer Science at Stanford University. He is affiliated with the Stanford AI Lab, Machine Learning Group and the Center for Research on Foundation Models. In the past, he served as a Chief Scientist at Pinterest and was an investigator at Chan Zuckerberg BioHub. Leskovec recently pioneered the field of Graph Neural Networks and co-authored PyG, the most widely-used graph neural network library. Research from his group has been used by many countries to fight COVID-19 pandemic, and has been incorporated into products at Facebook, Pinterest, Uber, YouTube, Amazon, and more.
His research received several awards including Microsoft Research Faculty Fellowship in 2011, Okawa Research award in 2012, Alfred P. Sloan Fellowship in 2012, Lagrange Prize in 2015, and ICDM Research Contributions Award in 2019. His research contributions have spanned social networks, data mining and machine learning, and computational biomedicine with the focus on drug discovery. His work has won 12 best paper awards and 5 10-year test of time awards at a premier venues in these research areas.
Leskovec received his bachelor's degree in computer science from University of Ljubljana, Slovenia, PhD in machine learning from Carnegie Mellon University and postdoctoral training at Cornell University. -
Marc Levenston
Associate Professor of Mechanical Engineering and, by courtesy, of Radiology (Radiological Sciences Laboratory)
Current Research and Scholarly InterestsMy lab's research involves the function, degeneration and repair of musculoskeletal soft tissues, with a focus on meniscal fibrocartilage and articular cartilage. We are particularly interested in the complex interactions between biophysical and biochemical cues in controlling cell behavior, the roles of these interactions in degenerative conditions such as osteoarthritis, and development of tissue engineered 3D model systems for studying physical influences on primary and progenitor cells.
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Craig Levin
Professor of Radiology (Molecular Imaging Program at Stanford/Nuclear Medicine) and, by courtesy, of Physics, of Electrical Engineering and of Bioengineering
Current Research and Scholarly InterestsMolecular Imaging Instrumentation
Laboratory
Our research interests involve the development of novel instrumentation and software algorithms for in vivo imaging of cellular and molecular signatures of disease in humans and small laboratory animal subjects. -
Philip Levis
Professor of Computer Science and of Electrical Engineering
BioProfessor Levis' research focuses on the design and implementation of efficient software systems for embedded wireless sensor networks; embedded network sensor architecture and design; systems programming and software engineering.
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Raymond Levitt
Kumagai Professor in the School of Engineering, Emeritus
Current Research and Scholarly InterestsDr. Levitt founded and directs Stanford’s Global Projects Center (GPC), which conducts research, education and outreach to enhance financing, governance and sustainability of global building and infrastructure projects. Dr. Levitt's research focuses on developing enhanced governance of infrastructure projects procured via Public-Private Partnerships (PPP) delivery, and alternative project delivery approaches for complex buildings like full-service hospitals or data centers.
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Marc Levoy
VMware Founders Professor in Computer Science and Professor of Electrical Engineering, Emeritus
BioLevoy's current interests include the science and art of photography, computational photography, light field sensing and display, and applications of computer graphics in microscopy and biology.
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Adrian Lew
Professor of Mechanical Engineering
BioProf. Lew's interests lie in the broad area of computational solid mechanics. He is concerned with the fundamental design and mathematical analysis of material models and numerical algorithms.
Currently the group is focused on the design of algorithms to simulate hydraulic fracturing. To this end we work on algorithms for time-integration embedded or immersed boundary methods. -
Fei-Fei Li
Sequoia Capital Professor, Denning Co-Director (On Leave) of Stanford HAI, Senior Fellow at HAI and Professor, by courtesy, of Operations, Information and Technology at the Graduate School of Business
On Partial Leave from 01/01/2024 To 12/31/2025Current Research and Scholarly InterestsAI, Machine Learning, Computer Vision, Robotics, AI+Healthcare, Human Vision
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Zhiye Li
Research Engineer
BioDr. Li is a research engineer in Civil and Environmental Engineering at Stanford University in the field of data-driven innovation and multiscale modeling on climate-resilient and sustainable civil infrastructures. She is also a researcher at the John A. Blume Earthquake Engineering Center at Stanford University and the Stanford Center at the Incheon Global Campus (SCIGC). Her interdisciplinary research integrates multiphysics model, machine learning, life cycle assessment and material innovation to accelerate the global net-zero transition. Within civil engineering, her research focuses on developing new building materials and building practices for more sustainable built environments. She researched at Hopkins Extreme Materials Institute and completed her Ph.D. in Civil Engineering at Johns Hopkins University.
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Percy Liang
Associate Professor of Computer Science, Senior Fellow at the Stanford Institute for HAI, and Associate Professor, by courtesy, of Statistics
BioPercy Liang is an Associate Professor of Computer Science at Stanford University (B.S. from MIT, 2004; Ph.D. from UC Berkeley, 2011) and the director of the Center for Research on Foundation Models (CRFM). He is currently focused on making foundation models (in particular, language models) more accessible through open-source and understandable through rigorous benchmarking. In the past, he has worked on many topics centered on machine learning and natural language processing, including robustness, interpretability, human interaction, learning theory, grounding, semantics, and reasoning. He is also a strong proponent of reproducibility through the creation of CodaLab Worksheets. His awards include the Presidential Early Career Award for Scientists and Engineers (2019), IJCAI Computers and Thought Award (2016), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), a Microsoft Research Faculty Fellowship (2014), and paper awards at ACL, EMNLP, ICML, COLT, ISMIR, CHI, UIST, and RSS.
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Michael Lin
Associate Professor of Neurobiology, of Bioengineering and, by courtesy, of Chemical and Systems Biology
Current Research and Scholarly InterestsOur lab applies biochemical and engineering principles to the development of protein-based tools for investigating biology in living animals. Topics of investigation include fluorescent protein-based voltage indicators, synthetic light-controllable proteins, bioluminescent reporters, and applications to studying animal models of disease.
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Aaron Lindenberg
Professor of Materials Science and Engineering and of Photon Science
BioLindenberg's research is focused on visualizing the ultrafast dynamics and atomic-scale structure of materials on femtosecond and picosecond time-scales. X-ray and electron scattering and spectroscopic techniques are combined with ultrafast optical techniques to provide a new way of taking snapshots of materials in motion. Current research is focused on the dynamics of phase transitions, ultrafast properties of nanoscale materials, and charge transport, with a focus on materials for information storage technologies, energy-related materials, and nanoscale optoelectronic devices.
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Christian Linder
Professor of Civil and Environmental Engineering and, by courtesy, of Mechanical Engineering
BioChristian Linder is a Professor of Civil and Environmental Engineering and, by courtesy, of Mechanical Engineering. Through the development of novel and efficient in-house computational methods based on a sound mathematical foundation, the research goal of the Computational Mechanics of Materials (CM2) Lab at Stanford University, led by Dr. Linder, is to understand micromechanically originated multi-scale and multi-physics mechanisms in solid materials undergoing large deformations and fracture. Applications include sustainable energy storage materials, flexible electronics, and granular materials.
Dr. Linder received his Ph.D. in Civil and Environmental Engineering from UC Berkeley, an MA in Mathematics from UC Berkeley, an M.Sc. in Computational Mechanics from the University of Stuttgart, and a Dipl.-Ing. degree in Civil Engineering from TU Graz. Before joining Stanford in 2013 he was a Junior-Professor of Micromechanics of Materials at the Applied Mechanics Institute of Stuttgart University where he also obtained his Habilitation in Mechanics. Notable honors include a Fulbright scholarship, the 2013 Richard-von-Mises Prize, the 2016 ICCM International Computational Method Young Investigator Award, the 2016 NSF CAREER Award, and the 2019 Presidential Early Career Award for Scientists and Engineers (PECASE). -
Scott W Linderman
Assistant Professor of Statistics and, by courtesy, of Computer Science and of Electrical Engineering
BioScott is an Assistant Professor of Statistics and, by courtesy, Electrical Engineering and Computer Science at Stanford University. He is also an Institute Scholar in the Wu Tsai Neurosciences Institute and a member of Stanford Bio-X and the Stanford AI Lab. His lab works at the intersection of machine learning and computational neuroscience, developing statistical methods to analyze large scale neural data. Previously, Scott was a postdoctoral fellow with Liam Paninski and David Blei at Columbia University, and he completed his PhD in Computer Science at Harvard University with Ryan Adams and Leslie Valiant. He obtained his undergraduate degree in Electrical and Computer Engineering from Cornell University and spent three years as a software engineer at Microsoft before graduate school.
