Stanford Doerr School of Sustainability
Showing 81-90 of 136 Results
-
Elizabeth Miller
Professor of Earth and Planetary Sciences, Emerita
Current Research and Scholarly InterestsStructural geology and tectonics. Evolution and deformation of continental crust and its sedimentary cover, plate tectonics and continental deformation, geochronology and thermochronology. Current interests in the Cordillera, northern circum-Pacific, Russia and Arctic regions.
-
J. Moldowan
Professor (Research) of Geological and Environmental Sciences, Emeritus
Current Research and Scholarly InterestsOrganic geochemistry; study of molecular fossils (biomarkers) and their use in petroleum system analysis, reservoir characterization, environmental monitoring, molecular paleontology, global change, petroleum biodegradation in reservoir. Studies of thermal cracking of petroleum by deep burial or catalytic alteration in deep source rocks and reservoirs by using diamondoids. Applications to unconventional petroleun exploration and development.
-
Tapan Mukerji
Professor (Research) of Energy Science Engineering, of Earth and Planetary Sciences and of Geophysics
Current Research and Scholarly InterestsMy students and I use theoretical, computational, and statistical models, to discover and understand fundamental relations between geophysical data and subsurface properties, to quantify uncertainty in our geomodels, and to address value of information for decision making under uncertainty.
-
Souradeep Mukherjee
Ph.D. Student in Earth and Planetary Sciences, admitted Autumn 2023
BioSouradeep is an Exploration Geologist-turned-AI Researcher developing decision-making algorithms to discover high-grade mineral deposits. With almost a decade of experience in on-field exploration of critical & strategic mineral deposits, he is now using his computer to unlock the full potential of mineral discovery.
Souradeep is currently a Doctoral Researcher at Stanford Mineral-X. His current work focuses on fusing multi-element soil geochemistry with 3D geological inference to build predictive models for subsurface intrusion-hosted Ni-Cu sulfide mineralization in the Curaçá Valley, Brazil. By leveraging machine learning, geostatistics, and compositional data analysis, he aims to reduce geological uncertainty and operational costs in mineral targeting, transforming how exploration is conducted in under-explored terrains.
Prior to Stanford, Souradeep held several technical and supervisory roles at the Atomic Minerals Directorate for Exploration and Research (AMD), Government of India, where he spearheaded multiple national-scale mineral exploration campaigns. He led the exploration and evaluation of uranium-bearing sediments in the Bhima Basin, the mapping of lithium-rich pegmatites in Karnataka, and the delineation of heavy mineral sand deposits across the east coast of India. His work included advanced geological mapping, structural interpretation, kinematic analysis, downhole geophysics, petrological microscopy, and geostatistical modeling—skills that now enrich his algorithmic thinking in research.
His research interests span compositional data analysis, geospatial modeling, machine learning for Earth systems, building intelligent decision making agents for mineral exploration and mineral prospectivity analysis. He is particularly passionate about bridging the gap between traditional geosciences and computational intelligence to power the next generation of resource discovery tools.
When he’s not deep into code or core samples, Souradeep contributes to scientific outreach, mentors young geoscientists, and advocates for data transparency and sustainability in the mining sector. He is also a writer, a poet and loves to write pieces on existential philosophy.
