Stanford Doerr School of Sustainability
Showing 1-10 of 25 Results
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Catherine (Hay) Callas
Ph.D. Student in Energy Resources Engineering, admitted Spring 2020
BioCatherine Callas is a Ph.D. candidate in the Benson Lab in Energy Resources Engineering. She is an ExxonMobil Emerging Energy Fellow, and her research is focused on offshore carbon capture and sequestration in the Gulf Coast. She obtained her M.S. degree in the Atmosphere and Energy program within Civil and Environmental Engineering from Stanford University and a B.S. degree in Chemical Engineering from Brown University. Before attending Stanford, she worked as a Financial Analyst within the Fixed Income group at Goldman Sachs in New York City for three years. She was a Schneider Fellow at the Natural Resources Defense Council in San Francisco where she analyzed the impact of the 2017 Northern California wildfires and 2018 Camp Fire on retail rates within PG&E’s service territory.
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Eeshan Chaturvedi
Ph.D. Student in Environment and Resources, admitted Autumn 2022
SGSI Student Assistant, Vice Provost for Graduate EducationBioEeshan is currently pursuing his Ph.D. in Climate Governance, and its correlations with policy, law, and earth systems. He holds an LLM in Environmental Law and Policy from Stanford Law School and has since worked with various domestic and international organizations on legal and management issues related to the environment and climate. In academia, he has held positions of Assistant Dean and Professor of Climate Governance and continues to engage with the various stakeholders in the climate space.
He enjoys discussions on neuroscience, astrophysics, and geo-politics in his free time. -
Zhenlin Chen
Ph.D. Student in Energy Resources Engineering, admitted Summer 2023
BioZhenlin (Richard) Chen is a Ph.D. candidate at Stanford's Adam Brandt lab, focuses on greenhouse gas emissions from oil and gas. His work primarily revolves around evaluating ground sensor technologies for methane detection and quantification ability. His methodological approach blends engineering principles, field data collection, and applied statistics. Chen is exploring AI-driven frameworks, particularly large language models, to refine energy data extraction and enhance the OPGEE model through private data fine-tuning and reinforcement learning. His emphasis remains on domain-specific tasks, aiming for efficiency in terms of latency and cost. He pursued his undergraduate studies in environmental science at Cornell University and holds a master's in Atmosphere and Energy Engineering from Stanford.
