Stanford Doerr School of Sustainability
Showing 1-10 of 22 Results
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Michelle María Early Capistrán
Social Science Research Scholar
BioMichelle María Early Capistrán is a David H. Smith Conservation Fellow at the Crowder Lab. Her transdisciplinary research focuses on working collaboratively with coastal communities to improve conservation practice by integrating Local Ecological Knowledge and marine ecology. She was originally trained as a Cultural Anthropologist and holds an M.S. and PhD in Marine Science and Limnology (Universidad Nacional Autónoma de México, UNAM). For over a decade, she has collaborated with rural fishing communities in the Baja California peninsula to understand long-term changes in the abundance of endangered and culturally important green turtles (Chelonia mydas). She will work with Prof. Crowder, in collaboration with Jeff Seminoff of the NOAA Southwest Fisheries Science Center, to develop species distribution model for green turtles under climate change by integrating Local Ecological Knowledge and Citizen/Community Science.
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Paul Ehrlich
Bing Professor of Population Studies, Emeritus
Current Research and Scholarly InterestsThe role of the social sciences in dealing with global change
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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
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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.
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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.
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Robin Elahi
Advanced Lecturer
BioI am an advanced lecturer at Stanford University’s Hopkins Marine Station, where I teach courses in kelp forest ecology, statistics, and scientific computing. In general, I study drivers of spatial and temporal change in marine ecosystems. Ongoing and recent research projects include:
-examining the consequences of fisheries closures on fisher behavior
-understanding why some coral reefs fare better than their neighbors
-biodiversity and body size change, particularly in the context of recent human impacts
