Stanford Doerr School of Sustainability
Showing 361-370 of 1,459 Results
-
Louis Durlofsky
Otto N. Miller Professor in the School of Earth Sciences
Current Research and Scholarly InterestsGeneral reservoir simulation, optimization, reduced-order modeling, upscaling, flow in fractured systems, history matching, CO2 sequestration, energy systems optimization
-
Michelle María Early Capistrán
Social Science Research Scholar
BioDr. Michelle María Early Capistrán is a Research Scientist at Stanford University's Environmental Social Sciences Department and an Affiliated Researcher at the Bill Lane Center for the American West. Her research addresses pressing issues in marine ecology under climate change by integrating transdisciplinary methods. She combines ethnobiological insights, historical data science, and ecological monitoring to understand and enhance the resilience of marine species and the coastal communities that depend on them, with a particular focus on the historical ecology and conservation of endangered green sea turtles. Dr. Early Capistrán earned her Ph.D. in Marine Science and Limnology from the Universidad Nacional Autónoma de México (UNAM) and is a recipient of the prestigious David H. Smith Conservation Research Fellowship.
-
Paul Ehrlich
Professor, Biology
Current Research and Scholarly InterestsThe role of the social sciences in dealing with global change
-
Marco Einaudi
Welton Joseph and Maud L'Anphere Crook Professor of Applied Earth Sciences, Emeritus
Current Research and Scholarly InterestsOre deposits and exploration; geology and geochemistry of hydrothermal mineral deposits
-
Kathleen Eisenhardt
Stanford W. Ascherman, M.D. Professor in the School of Engineering, Emerita
Current Research and Scholarly InterestsTheoretical approaches: Cognition, complexity, learning, and organizational theories
Methods: Multi-case Theory Building as well as machine learning, simulation, and econometrics
Recent research: Business model design, strategy as "simple rules" heuristics, strategic interaction in novel markets and ecosystems, strategy in marketplaces, communities v. firm organizational forms -
Abbas El Gamal
Hitachi America Professor in the School of Engineering and Senior Fellow at the Precourt Institute for Energy
BioAbbas El Gamal is the Hitachi America Professor in the School of Engineering and Professor in the Department of Electrical Engineering at Stanford University. He received his B.Sc. Honors degree from Cairo University in 1972, and his M.S. in Statistics and Ph.D. in Electrical Engineering both from Stanford University in 1977 and 1978, respectively. From 1978 to 1980, he was an Assistant Professor of Electrical Engineering at USC. From 2003 to 2012, he was the Director of the Information Systems Laboratory at Stanford University. From 2012 to 2017 he was Chair of the Department of Electrical Engineering at Stanford University. His research contributions have been in network information theory, FPGAs, and digital imaging devices and systems. He has authored or coauthored over 230 papers and holds 35 patents in these areas. He is coauthor of the book Network Information Theory (Cambridge Press 2011). He has received several honors and awards for his research contributions, including the 2016 Richard W. Hamming Medal, the 2012 Claude E. Shannon Award, and the 2004 INFOCOM Paper Award. He is a member of the U.S. National Academy of Engineering and a Fellow of the IEEE. He has co-founded and served on the board of directors and advisory boards of several semiconductor and biotechnology startup companies.
-
Lama El Halabi
Ph.D. Student in Energy Science and Engineering, admitted Spring 2022
BioI am a PhD candidate in the Department of Energy Sciences and Engineering and a Data Science Scholar, advised by Adam Brandt. My research is driven by the crucial role renewable energy must play in sustainably meeting our energy demands. The major challenge in transitioning to renewable energy lies in the intermittent and inherently uncertain nature of these energy sources. My current research focuses on predicting energy outputs from these stochastically behaving sources, with an emphasis on uncertainty quantification and volatility. Specifically, I employ computer vision models and statistical techniques to develop short-term probabilistic photovoltaic (PV) power forecasts from sky images and time-series PV data. I hold an MS in Energy Resources Engineering from Stanford and a BE in Mechanical Engineering and a BS in Physics from the American University of Beirut. Previously, my research involved using machine learning to model water resources.
