Stanford Doerr School of Sustainability
Showing 1-10 of 18 Results
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Carlos Alvarez Zambrano
Postdoctoral Scholar, Geological Sciences
BioCarlos' research interests include granular matter transport, sand dunes, multiphase flows, and the transport of particles in the atmosphere. At Stanford, Carlos is investigating the formation of eolian bedforms on Mars and Earth.
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Adel Asadi
Postdoctoral Scholar, Earth and Planetary Sciences
BioAdel Asadi is a Postdoctoral Scholar at Stanford University's Department of Earth and Planetary Sciences, in the Doerr School of Sustainability. He is an affiliate member of the Mineral-X Initiative, a program dedicated to pioneering sustainable critical minerals exploration to facilitate the transition to green energy. Under the supervision of Prof. Jef Caers, Adel's research is focused on mineral exploration, leveraging data science tools and artificial intelligence algorithms. Through the integrated geological data analysis, his goal is to enhance the predictive accuracy of models for discovering high-grade mineral deposits, thereby enabling decision-making with higher certainty.
Before joining Stanford University, Adel was a Postdoctoral Scholar at Tufts University in Massachusetts. There, he conducted research in natural hazards and renewable energy domains. Under Prof. Laurie Baise’s supervision, he developed a novel ensemble machine learning method to assess earthquake-induced soil liquefaction hazards, notably for the 2023 Türkiye Earthquakes. Under Prof. Babak Moaveni’s supervision, in a project funded by the National Science Foundation (NSF), he exploited multiple-point geostatistics to simulate offshore wind speed and direction in a multi-variate context, using numerical weather models, remote sensing, observational, and geospatial data.
Adel Asadi earned his PhD in Civil and Environmental Engineering with a Geosystems specialization from Tufts University. His doctoral work in the Geohazards Research Lab involved a diverse toolkit (computer vision, machine learning, remote sensing, and geographic information systems) to model earthquake-induced ground failure hazards (soil liquefaction) and map post-earthquake ground failure damages (landslides and liquefaction) on global, regional, and event-specific scales. His dissertation research was funded by the US Geological Survey (USGS) and the National Geospatial Intelligence Agency (NGIA).
During his Master's study in Mining Engineering at Michigan Technological University, under Prof. Snehamoy Chatterjee’s supervision, he developed a novel multiple-point geostatistical simulation algorithm for Earth resources modeling and uncertainty quantification. He also worked on a space mining research project aimed at mapping iron and titanium on the lunar surface using remote sensing data and machine learning algorithms. Additionally, he gained one year of professional experience in the copper mining industry through three internships at Freeport-McMoRan Inc. in Arizona. -
Amir Eskanlou
Postdoctoral Scholar, Earth and Planetary Sciences
BioAmir specializes in mineral & metallurgical processing, and computational materials science. At Stanford, one of his research projects is to employ AI-accelerated DFT computations, MD simulations, and generative chemistry to develop innovative chemicals and ligands for the selective recovery of critical energy transition minerals and metals from both primary and secondary resources. Amir is also working on supply chain modeling and the intelligent design of processing operations under uncertainty for critical minerals.
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Tianyang Guo (郭天阳)
Postdoctoral Scholar, Geological Sciences
BioDr. Tianyang Guo earned his Ph.D. degree in Rock Mechanics from the Department of Earth Sciences, the University of Hong Kong in 2020. He earned his bachelor's and master’s degree from Wuhan University (WHU) in 2013 and 2016, respectively. He was awarded the National Scholarship for Graduate in 2015 and graduated from WHU as an outstanding graduate. Before joining Stanford, he was a Postdoctoral Fellow in the Department of Civil and Environmental Engineering at the Hong Kong Polytechnic University (PolyU) under PolyU Distinguished Postdoctoral Fellowship Scheme 2021.
His research interests include (1) Cracking mechanisms and induced microseismicity during the injection of CO2 into reservoir rocks. (2) Application of machine learning in acoustic emission (AE) data interpretation. (3) Microcracking mechanisms of granite based on AE and microscopic observation. -
Jonas Kloeckner
Postdoctoral Scholar, Earth and Planetary Sciences
BioJonas Kloeckner is a Postdoctoral Fellow at the Stanford Doerr School of Sustainability, sponsored by the Stanford Institute for Human-Centered Artificial Intelligence (HAI). He specializes in critical mineral exploration essential for the sustainable energy transition. Utilizing his expertise in artificial intelligence and resource forecasting, Mr. Kloeckner leads initiatives that strive to align with global sustainability goals.
Jonas earned his PhD in Engineering from the Federal University of Rio Grande do Sul (UFRGS), Brazil, where he later served as a Postdoctoral Fellow at the Institute of Geosciences. His doctoral and postdoctoral research focused on advancing geostatistical methods for Earth resources forecasting, significantly contributing to the field.
Previously, Jonas was a Visiting Research Scholar at Stanford University under the mentorship of Professor Jef Caers. He holds a Master’s and Bachelor’s degree in Mining Engineering from UFRGS, with additional international studies at Ecole des Mines d’Alès, France, and as a visiting student at Columbia University, USA.
Jonas’s current research integrates spatial data analysis with advanced decision-making processes in subsurface systems, enhancing resource management strategies and supporting sustainable mining practices. Beyond academia, he actively collaborates on various international projects, optimizing resource extraction and minimizing environmental impacts through innovative technology and interdisciplinary collaboration.