Stanford Doerr School of Sustainability
Showing 1-50 of 69 Results
-
Ammar Alali
Ph.D. Student in Energy Science and Engineering, admitted Autumn 2023
BioI'm Ammar, a PhD student in Energy Science Engineering who is working with Hamdi Tchelepi. I got my master's degree from Stanford in 2018, and since then I have been working with Aramco as part of the development teams of two projects for Underground Gas Storage and CCUS to be developed for the first time in Saudi Arabia. My masters research was focused on numerical reservoir simulation of capillary-dominated flow in matrix-fracture systems using interface conditions. In my free time, I enjoy reading modern poetry and watching classic films.
-
Isabela Beine
Ph.D. Student in Energy Science and Engineering, admitted Spring 2026
Masters Student in Energy Science and Engineering, admitted Autumn 2024BioResearching hydrogen storage in porous media. Interest in energy storage solutions for renewable energy sources.
-
Dylan Marshall Crain
Ph.D. Student in Energy Resources Engineering, admitted Autumn 2022
Current Research and Scholarly InterestsMy current research revolves around optimizing the monitoring design of Carbon Capture and Sequestration (CCS) projects in such a way that the posterior (after data assimilation) predictions are as close to reality as can be hoped for.
In CCS projects within the U.S., it is important to have monitoring plan, which can consist of wells with pressure, saturation, salinity, et cetera sensors, seismic lines, or gravimetric above-ground measurements, before any injection has begun into the subsurface. This is due to the permitting requirements that must be satisfied before operations are begun.
Due to this constraint, any monitoring optimization (at least initially) needs to be determined using only a prior (highly uncertain) understanding of the subsurface. This makes the optimization much more challenging. We utilize a prior optimization scheme from a previous student which allows us to optimize a monitoring plan using only prior information to get the minimized, expected uncertainty reduction in the posterior models for a given quantity of interest. This scheme is limited by some Gaussian assumptions. We optimize it using a genetic algorithm.
From this point, with the monitoring plan established, the information gathered from the optimized monitoring scheme (using only monitoring wells at the moment) is used to history match (data assimilate) our understanding of the subsurface. The results can be used to predict the CO2 plume flow and behavior into the future.
This work was initially developed to assist a project in Illinois that is currently seeking Class VI injection well permits in the self-same state in order to begin injecting CO2 produced from two companies paying for the work from the Illinois Geological Survey. -
Victoria Dinov
Masters Student in Energy Science and Engineering, admitted Autumn 2025
BioHi, my name is Vicky and I am a graduate student at Stanford studying energy science and engineering. At Stanford, I worked in the INES research group, focused primarily on creating a capacity expansion model with improved spatial, temporal, and geographical resolution.
I am passionate about capacity expansion and transmission planning, power markets, utility rate structure, load forecasting, microgrids and more. I am also curious to explore the ways in which we will harness DERs and technological tools at our fingertips to create more resilient communities and energy systems. This can have broad implications for developing regions and more generally energy scarce areas.
Outside of school, you will find me running, climbing, backpacking, skiing, etc. I like everything outdoors, have an affinity for art/music, and love to salsa too. Please message me with questions or just to connect! -
Lama El Halabi
Ph.D. Student in Energy Science and Engineering, admitted Spring 2022
BioI am a PhD candidate in the Department of Energy Sciences and Engineering and a Data Science Scholar, advised by Adam Brandt. My research is driven by the crucial role renewable energy must play in sustainably meeting our energy demands. The major challenge in transitioning to renewable energy lies in the intermittent and inherently uncertain nature of these energy sources. My current research focuses on predicting energy outputs from these stochastically behaving sources, with an emphasis on uncertainty quantification and volatility. Specifically, I employ computer vision models and statistical techniques to develop short-term probabilistic photovoltaic (PV) power forecasts from sky images and time-series PV data. I hold an MS in Energy Resources Engineering from Stanford and a BE in Mechanical Engineering and a BS in Physics from the American University of Beirut. Previously, my research involved using machine learning to model water resources.
-
Julia Frohmann
Ph.D. Student in Energy Science and Engineering, admitted Autumn 2023
BioJulia Frohmann is a PhD candidate in Energy Science and Engineering, and leads the demand side technology utilization modeling at STEER. Her research focuses on the feasibility of large-scale grid storage deployment in the US by evaluating battery energy storage revenue generation potential. Julia's key areas of interest are electricity market operations, and macro-scale energy systems modeling. Previous work focused on renewable grid penetration effect on electricity exchange variability and modeling optimal integration of power-to-heat-to-power storage. Julia obtained her bachelors in Mechanical Engineering and masters in Energy Engineering from RWTH Aachen, Germany.
-
Halldora Gudmundsdottir
Ph.D. Student in Energy Resources Engineering, admitted Autumn 2014
Current Research and Scholarly InterestsMy PhD research focuses on developing predictive models for geothermal systems. I am interested in direct predictions of the future performance of geothermal reservoirs as well as characterization of the subsurface flow behavior that can aid in operational decision making. Currently, I am incorporating principles from statistics and artificial intelligence into workflows that can be used for production and injection optimization.
-
Mathis Heyer
Ph.D. Student in Energy Science and Engineering, admitted Autumn 2024
BioMathis Heyer, from Kiel, Germany, is pursuing a Ph.D. in Energy Science & Engineering at the Stanford Doerr School of Sustainability. He holds a bachelor’s degree in Mechanical Engineering and a master’s degree in Process Systems Engineering from RWTH Aachen University, Germany, as well as a master’s degree in Management Science and Engineering from Tsinghua University in Beijing.
His research in the Environmental Assessment and Optimization Group at Stanford (https://eao.stanford.edu/) focuses on advancing the understanding of complex energy and process systems through mathematical modeling and optimization. Mathis' work builds on his previous research experiences at the Climate Policy Lab at ETH Zurich and the Sustainable Reaction Engineering Group at Cambridge University. Outside of his academic pursuits, Mathis enjoys volunteering with organizations such as "Engineers Without Borders" and "Europe Meets School" both involved in promoting intercultural exchange.
Mathis has been recognized as a Klaus-Murmann Fellow by the Foundation of German Business (sdw) while at RWTH Aachen and is currently an ERP Fellow with the German Academic Scholarship Foundation and a recipient of the SGF Fellowship. -
Shaunak Joshi
Ph.D. Student in Energy Science and Engineering, admitted Autumn 2022
BioI am Shaunak, from India. I am starting my PhD in Energy Science and Engineering with Prof. Daniel Tartakovsky and Prof. Hamdi Tchelepi. My research will primarily focus on pore-scale modeling of lithium-based batteries.
Prior to this, I graduated from the Indian Institute of Technology (IIT) Bombay with a Bachelor's and a Master's in Energy Science and Engineering. I love to play all sorts of sports, especially football, badminton, and cricket. You would usually see me running around the campus on odd days. Hit me up if you want to have a chat! -
Filippos Kostakis
Ph.D. Student in Energy Resources Engineering, admitted Winter 2020
Current Research and Scholarly InterestsMutlifidelity strategies for uncertainty quantification, data assimilation and optimization in oil and gas reservoirs.
-
Audrey McManemin
Ph.D. Student in Energy Science and Engineering, admitted Spring 2025
BioAudrey is pursuing a master's degree in Energy Science & Engineering and is expecting to graduate in Spring 2025. She holds a B.S.E in Mechanical Engineering from Duke University and has previously worked in data engineering. Her research at Stanford focuses on evaluating methane detection and quantification technologies currently used in both commercial and academic applications.
-
Frances Reuland
Ph.D. Student in Energy Science and Engineering, admitted Spring 2025
BioFran, from Chapel Hill, North Carolina, is a PhD student in Energy Science & Engineering at Stanford University. She completed her MS in the same department in 2025 and was named as a 2023 Knight Hennessy Scholar. Before becoming a Stanford student, she spent three years at the Rocky Mountain Institute (RMI) in Boulder, Colorado working on decarbonization solutions for the oil and gas sector. She has a particular focus on methane detection, mitigation, and policy solutions. Prior to RMI, she held a position at the International Energy Agency (IEA) in Paris, France working to support IEA's work on methane from the petroleum sector.
She is a graduate and varsity women's soccer player of the University of North Carolina-Chapel Hill. Fran earned a B.S. with High Honors in Environmental Science, a Chemistry minor, and a B.A. in Spanish. She has continued her love for competitive soccer career playing in France, Colorado, and California.
