Stanford Doerr School of Sustainability
Showing 111-120 of 121 Results
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Sandeep Yadav
Postdoctoral Scholar, Energy Science and Engineering
BioSandeep Yadav is a postdoctoral scholar in the Department of Energy Resources Engineering at the Stanford Doerr School of Sustainability. His research focuses on advancing sustainable energy systems, with an emphasis on techno-economic analysis and modeling of carbon capture retrofits for industrial decarbonization and energy efficiency. He earned his Ph.D. in Energy Science and Engineering from the Indian Institute of Technology (IIT) Bombay, where he specialized in the techno-economic assessment of carbon capture technologies, data center cooling, and combined cooling and power systems. Sandeep is committed to supporting the global transition to low-carbon energy and is passionate about mentoring the next generation of scientists and engineers.
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Weiwei Zhan
Postdoctoral Scholar, Earth System Science
BioI study the coupling between the global carbon and water cycles under climate change. Specifically, I investigate how plants regulate carbon uptake and water loss as atmospheric CO2 rises and water limitation intensifies, and how these responses feed back on the global environment. I develop hybrid physics–machine learning approaches and combine them with the expanding record of satellite and in situ observations to test hypotheses about ecosystem function.
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Aidi Zhang
Postdoctoral Scholar, Geophysics
BioI am interested in the fluid dynamics in geophysical and astrophysical systems. You can find more details on my website (https://aidi-zhang.github.io/)
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Zhenglin Zhang
Postdoctoral Scholar, Earth System Science
Current Research and Scholarly InterestsClimate change mitigation and sustainable nutrient management in agroecosystems
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Xiaojian Zheng
Postdoctoral Scholar, Earth System Science
BioDr. Xiaojian Zheng is a postdoctoral scholar in the Department of Earth System Science at Stanford University, working with Dr. Yuan Wang. His research targets aerosol–cloud–climate interactions, combining ground-based, airborne, and satellite observations with global and convection-permitting models, and leveraging machine learning throughout the analysis.
Xiaojian's current research directions span deep learning-based estimates of regime-dependent aerosol–cloud interactions, machine-learning emulation of aerosol microphysics inside Earth System models, and the circulation control of convection, heatwaves, and regional air quality.
