School of Engineering
Showing 191-200 of 535 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. -
Marlys LeSene
Program Director, Communications & Initiatives, Bioengineering
Current Role at StanfordProgram Director, Communications & Initiatives
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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.
