Stanford Doerr School of Sustainability
Showing 1-18 of 18 Results
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Matteo Frigo
Postdoctoral Scholar, Energy Resources Engineering
BioMatteo Frigo has been a postdoctoral researcher in the Department of Energy Science and Engineering at Stanford University since August 2023.
He received his Bachelor's and Master's degrees in civil engineering from the University of Padua in 2014 and 2017, respectively.
In 2020, he received his Ph.D. degree from the University of Padua, with a major in Numerical Analysis.
During his Ph.D., he spent a period as a Visiting Researcher Student at Lawrence Livermore National Laboratory (LLNL), California, USA.
His leading scientific interests include mathematical and numerical modeling of multiphysics problems mainly related to poromechanics and fracture mechanics.
His research mainly focuses on studying numerical linear algebra problems and preconditioning techniques.
He has experience in implementing high-performance parallel codes on supercomputers with distributed memory and GPU accelerators. -
Laura Frouté
Postdoctoral Scholar, Energy Science and Engineering
Current Research and Scholarly InterestsLaura is a postdoctoral scholar at Stanford University, working on subsurface engineering solutions for the energy transition. Part of her research focuses on replicating geological hydrogen production in the laboratory and identifying and mitigating reactivity constraints at the microscale. Her research also focuses on investigating carbon storage into various basalt formations by measuring their carbon mineralization potential. Her expertise includes designing laboratory-scale pilots and conducting research on rock formations in the context of hydrocarbon production, carbon storage, and hydrogen production to understand the interplay of geochemistry, reaction mechanisms and complex storage and transport processes across length scales. To study the evolution of porous media properties following reaction or transport experiments, she uses a wide spectrum of multiscale, multimodal material characterization techniques (sorption, XRD, XRF, μCT, FIB-SEM, TEM). She holds a MS in Chemical Engineering from ENSIC (France) and a PhD in Energy Science and Engineering from Stanford University. Her interests range from subsurface engineering, fluid flow in porous media, to environmental and regulatory issues in the oil & gas industry, CCUS, climate solutions and energy policy.
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Qi Hu
Postdoctoral Scholar, Energy Science and Engineering
BioI am a postdoctoral scholar collaborating with Tapan Mukerji on developing innovative workflows for monitoring subsurface CO2 sequestration. My research primarily involves integrating advanced seismic inversion techniques, such as full-waveform inversion, with rock physics and fluid dynamics to glean insights into subsurface structures and behaviors. Additionally, I am intrigued by the potential of distributed acoustic sensing and machine learning algorithms in various topics related to energy transition.
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Lane D. Smith
Postdoctoral Scholar, Energy Science and Engineering
BioLane D. Smith is a postdoctoral scholar working with the Climate and Energy Policy Program at Stanford University. His research interests include energy policy, electricity rate design, energy affordability, and macro-energy systems (with a particular focus on the electric grid). Lane holds a Ph.D. and M.S. in Electrical Engineering from the University of Washington (2024 and 2019, respectively) and a B.S. in Electrical Engineering from the University of Denver (2018).
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Suihong Song
Postdoctoral Scholar, Energy Resources Engineering
BioSuihong Song collaborates with Professor Tapan Mukerji at the Stanford Center for Earth Resources Forecast (SCERF) as a postdoctoral scholar. His research is centered on integrating machine learning with geosciences, specifically focusing on machine learning-based reservoir characterization and geomodelling, Physics-informed Neural Networks (PINNs) and neural operators as well as their applications in porous flow simulations, neural networks-based surrogate and inversion, decision-making under uncertainty, and machine learning-based geological interpretation of well logs and seismic data. These research endeavors have practical applications in managing underground water resources, oil and gas exploration, geological storage of CO2, and the evaluation of hydrothermal and natural hydrogen, among others.Song proposed GANSim, an abbreviation for Generative Adversarial Networks-based reservoir simulation, which presents a reservoir geomodelling workflow. This innovative approach has been successfully implemented in various 3D field reservoirs by international oil companies, including ExxonMobil.
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Alexis Pengfei Zhao
Postdoctoral Scholar, Energy Science and Engineering
BioAlexis Pengfei Zhao was born in Beijing, China. He received the B.Eng. and Ph.D. degrees from the University of Bath, U.K., in 2017 and 2021, respectively. In 2019, he was a visiting Ph.D. student at the Smart Grid Operations and Optimization Laboratory (SGOOL), Tsinghua University, Beijing, China. From 2021 to 2024, he was an Associate Professor at the Institute of Automation, Chinese Academy of Sciences, Beijing, China. In 2024, he joined Cornell University, Ithaca, NY, USA, as an Ezra SYSEN Research Associate of System Engineering.
Dr. Zhao is now a Postdoctoral Research Associate in the Department of Energy Science and Engineering, Stanford Doerr School of Sustainability, Stanford University, Stanford, CA, USA. His major research interests include Net Zero Energy Systems and Cyber-Physical-Social Systems.
