School of Engineering
Showing 51-100 of 248 Results
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William Abraham Tarpeh
Assistant Professor of Chemical Engineering, by courtesy, of Civil and Environmental Engineering and Center Fellow at the Precourt Institute for Energy and, by courtesy, at the Woods Institute for the Environment
BioReimagining liquid waste streams as resources can lead to recovery of valuable products and more efficient, less costly approaches to reducing harmful discharges to the environment. Pollutants in effluent streams can be captured and used as valuable inputs to other processes. For example, municipal wastewater contains resources like energy, water, nutrients, and metals. The Tarpeh Lab develops and evaluates novel approaches to resource recovery from “waste” waters at several synergistic scales: molecular mechanisms of chemical transport and transformation; novel unit processes that increase resource efficiency; and systems-level assessments that identify optimization opportunities. We employ understanding of electrochemistry, separations, thermodynamics, kinetics, and reactor design to preferentially recover resources from waste. We leverage these molecular-scale insights to increase the sustainability of engineered processes in terms of energy, environmental impact, and cost.
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Daniel Tartakovsky
Professor of Energy Science Engineering
Current Research and Scholarly InterestsEnvironmental fluid mechanics, Applied and computational mathematics, Biomedical modeling.
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Clyde Tatum
Obayashi Professor in the School of Engineering, Emeritus
BioTatum's teaching interests are construction engineering and technical construction. His research focuses on construction process knowledge and integration and innovation in construction.
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Søren Henri Taverniers
Physical Science Research Scientist
Current Research and Scholarly InterestsDesign and implementation of novel statistical algorithms based on the Multilevel Monte Carlo method to accelerate the quantification of uncertainty in quantities of interest for multiphase systems such as reactive granular media and subsurface flows.
Development of neural-network based surrogate approaches to enable data-driven sensitivity analysis and uncertainty quantification for multiscale systems such as energy storage systems, and accelerate the design process of such devices. -
Hamdi Tchelepi
Max Steineke Professor and Senior Fellow at the Precourt Institute for Energy
Current Research and Scholarly InterestsCurrent research activities: (1) model and simulate unstable miscible and immiscible fluid flow in heterogeneous porous media, (2) develop multiscale numerical solution algorithms for coupled mechanics and multiphase fluid flow in large-scale subsurface formations, and (3) develop stochastic solution methods that quantify the uncertainty associated with predictions of fluid-structure dynamics in porous media.
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Kamran Tehranchi
Ph.D. Student in Civil and Environmental Engineering, admitted Autumn 2023
BioKamran Tehranchi is a Ph.D. Student in Civil & Environmental Engineering at Stanford University researching planning processes for decarbonized and reliable electricity systems. His work focuses on developing energy system optimization models to support policy analysis. He has previously worked in the public sector as a Shultz Energy Fellow at the California Independent System Operator (CAISO), an analyst at a Community Choice Aggregator (CCA), and within city and county governments. He is a member of the Interdisciplinary Energy Systems research group, advised by Professor Ines Azevedo. He holds a M.S. in Civil & Environmental Engineering from Stanford University and a B.S. in Mechanical Engineering at Northwestern University.
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Jay Prakash Thakur
Graduate, Stanford Center for Professional Development
BioJay Prakash Thakur is a Senior Machine Learning Engineer at Microsoft specializing in AI agents, multi-agent systems, and responsible agentic AI innovation. Featured in WIRED Magazine for insights on AI agent accountability and the Stanford LEAD Quarterly, Jay bridges technical excellence with strategic thinking to shape the future of human-AI collaboration.
As an open-source contributor to leading agentic frameworks and advisor to industry committees, he focuses on building scalable systems that drive business growth while serving society ethically. His deep expertise spans agentic AI architecture, multi-agent systems, big data, deep learning, and machine learning.
Previously built scalable AI/ML solutions at Amazon and Accenture, Jay has published research on frontier technologies and actively contributes to leading tech communities including IEEE (Senior Member), ACM, and AAAI. He serves as a business and startup advisor, holds multiple patents, and is a global speaker, conference session chair, and panelist on Agentic AI innovation and ethics.
With thought leadership articles reaching global readers and trending on major tech platforms, Jay has established himself as a prominent voice shaping the future of agentic AI development at the intersection of innovation, strategic leadership, and responsible technology.
