School of Engineering
Showing 1-22 of 22 Results
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Sho Takatori
Associate Professor of Chemical Engineering
BioPeople say that a picture is worth a thousand words. We think that an equation is worth a thousand pictures. Literally. By collecting and processing data-rich images of complex fluids and matter, we develop “picture-perfect” equations to learn structure-property relationships for new material innovation.
In the Takatori lab, we combine theory, simulation, and experiment to discover mathematical models for complex fluids in engineered and natural environments. We use advanced microscopy and analyze pictures with data-driven methods to understand material properties that bridge the microscopic-to-continuum scales. Our research encompasses soft squishy materials like polymers and liquid crystals, as well as granular matter like sand, powders, and foams.
Outside of research, I have had a strong passion for public speaking since high school, taking speech courses in college and competing in speech contests in Toastmasters International (a professional organization to improve public speaking and leadership skills) for several years as a PhD student. More recently, as a professor and educator, I have channeled my passion for speaking towards science education and technical communication. I have always believed that effective science communication can make broad impacts to society by building public trust in science, promoting data-driven decisions in government and industry, and improving the accessibility of science to all communities. I look forward to continue working on effective science communication skills and storytelling techniques with Stanford graduate students and researchers. -
Thierry Tambe
Assistant Professor of Electrical Engineering and, by courtesy, of Computer Science
BioThierry Tambe is an Assistant Professor of Electrical Engineering and, by courtesy, of Computer Science, and the William George and Ida Mary Hoover Faculty Fellow at Stanford University. His research centers on co-designing algorithms and hardware—from high-level models down to custom silicon—to enable efficient execution of AI and data-intensive workloads, with memory efficiency as a central theme. His work has been recognized through an NSF CAREER Award, the inaugural Google ML and Systems Junior Faculty Award, an NVIDIA Graduate PhD Fellowship, an IEEE SSCS Predoctoral Achievement Award, and several distinguished paper awards. Previously, Thierry was a visiting research scientist at NVIDIA and an engineer at Intel. He received a B.S. and M.Eng. from Texas A&M University, and a PhD from Harvard University, all in Electrical Engineering.
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Li-Yang Tan
Associate Professor of Computer Science
Current Research and Scholarly InterestsTheoretical computer science, with an emphasis on complexity theory
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Sindy Tang
Associate Professor of Mechanical Engineering, Senior Fellow at the Woods Institute for the Environment and Professor, by courtesy, of Radiology and of Bioengineering
Current Research and Scholarly InterestsProf. Sindy K.Y. Tang develops engineering platforms that measure biological systems and convert these measurements into quantitative datasets. Her research focuses on experimental systems that probe biological processes across cellular and tissue scales, particularly how physical context—geometry, mechanics, and spatial organization—shapes biological function. Current work spans immune diagnostics, spatial tissue sampling for multi-omics analysis, and single-cell perturbation studies.
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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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Hawa Racine Thiam
Assistant Professor of Bioengineering and of Microbiology and Immunology
Current Research and Scholarly InterestsOur current work has two branches. Branch #1 is building a quantitative and predictive understanding of how neutrophils initiate and complete NETosis. Branch #2 is identifying the molecular and biophysical mechanisms that regulate high deformability in neutrophils. These branches converge onto understanding and harnessing the impact of nuclear biophysics on immune cell functions to re-engineer neutrophils for improved health.
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Fouad Tobagi
Professor of Electrical Engineering
On Leave from 10/01/2025 To 06/30/2026BioTobagi works on network control mechanisms for handling multimedia traffic (voice, video and TCP- based applications) and on the performance assessment of networked multimedia applications using user-perceived quality measures. He also investigates the design of wireless networks, including QoS-based media access control and network resource management, as well as network architectures and infrastructures for the support of mobile users, all meeting the requirements of multimedia traffic. He also investigates the design of metropolitan and wide area networks combining optical and electronic networking technologies, including topological design, capacity provisioning, and adaptive routing.
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George Toye
Adjunct Professor
BioGeorge Toye, Ph.D., P.E., is adjunct professor in Mechanical Engineering at Stanford University.
While teaching advanced project-based engineering design thinking and STEM-based innovations at the graduate level as part of ME310, he also contributes to research in varied topics in engineering education, and effective globally-distributed team collaborations. As well, he remains active in entrepreneurship and varied advising/consulting work.
George earned his B.S. and M.S. degrees in Mechanical Engineering from U.C. Berkeley, and Ph.D. in Mechanical Engineering with minor in Electrical Engineering from Stanford University.
Since 1983, he has enjoyed volunteering annually to organize regional and state-level Mathcounts competitions to promote mathematics education amongst middle-school aged students. -
Brian Trippe
Assistant Professor of Statistics and, by courtesy, of Computer Science
BioDr. Brian Trippe is an assistant professor at Stanford in the Department of Statistics, with an affiliation in Stanford Data Science.
In his research, Dr. Trippe develops probabilistic machine learning methods to address challenges in biotechnology and medicine. Recently, his focus has been on generative modeling and inference algorithms for protein engineering.
Before joining Stanford, Dr. Trippe was a postdoctoral fellow at Columbia University in the Department of Statistics, and a visiting researcher at the Institute for Protein Design at the University of Washington. -
Caroline Trippel
Assistant Professor of Computer Science and of Electrical Engineering
BioCaroline Trippel is an Assistant Professor in the Computer Science and Electrical Engineering Departments at Stanford University, where she leads the High Assurance Computer Architectures Lab. Following her PhD, prior to starting at Stanford, Trippel spent nine months as a Research Scientist at Facebook in the FAIR SysML group. Trippel's research fits broadly in the area of computer architecture and focuses on promoting high assurance—correctness, security, and reliability—as a first-order computer architecture design goal. A central theme of her work is leveraging formal methods, especially automated reasoning, techniques to design and verify hardware systems. Trippel research has influenced the design of the RISC-V ISA memory consistency model both via her formal analysis of its draft specification and her subsequent participation in the RISC-V Memory Model Task Group; prompted Intel to update their Software Security Guidance to confirm that two Intel microarchitectures satisfy assumptions made by the Seberus Spectre defense that her lab developed; and produced a novel methodology and tool that synthesized two new variants of the famous Meltdown and Spectre attacks. Trippel's research has been recognized with IEEE Top Picks distinctions, a Sloan Research Fellowship, an NSF CAREER Award, the inaugural Google ML and Systems Junior Faculty Award, the Intel Rising Star Faculty Award, an Intel Outstanding Researcher Award, the 2020 ACM SIGARCH/IEEE CS TCCA Outstanding Dissertation Award, the 2020 CGS/ProQuest® Distinguished Dissertation Award in Mathematics, Physical Sciences, & Engineering, and more.
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Nick Troccoli
Lecturer
BioNick Troccoli is a Lecturer in the Stanford Computer Science Department. He started as a full-time lecturer at Stanford in Fall 2018, after graduating from Stanford in June 2018 with Bachelor's and Master's Degrees in Computer Science. He has taught CS106X, CS107, CS110 and CS111. In 2022, 2024 and 2025 he was named to the Tau Beta Pi Teaching Honor Roll. During his undergraduate career, he specialized in Systems, and during his graduate career he specialized in Artificial Intelligence. He was heavily involved in teaching as both an undergraduate and graduate student; he was an undergraduate Section Leader in the CS 198 Section Leading Program, a graduate CA (Course Assistant) for CS 181, the Head TA for CS 106A and CS 106B, and the summer 2017 instructor for CS 106A. In 2017 he was awarded the Forsythe Teaching Award and the Centennial TA Award for excellence in teaching.
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Stephen Tsai
Professor (Research) of Aeronautics and Astronautics, Emeritus
BioProfessor Tsai's research interest is in the development of design methodology of composite materials and structures. As an emerging technology, composite materials offer unique performances for structures that combine light weight with durability. Keys to the successful utilization of composite materials are predictability in performance and cost effective design of anisotropic, laminated structures. Current emphasis is placed on the understanding of failure modes, and computer simulation for design and cost estimation.
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Edison Tse
Associate Professor of Management Science and Engineering, Emeritus
BioProfessor Edison Tse received his BS, MS, and Ph.D. in Electrical Engineering from Massachusetts Institute of Technology. He is the Director of Asia Center of Management Science and Engineering, which has the charter of developing executive training programs for executives in Asian enterprises, conducting research on development of the emerging economy in Asia and establishing research affiliations with Asian enterprises, with a special focus in Greater China: China, Hong Kong, and Taiwan.
In 1973, he received the prestigious Donald Eckman Award from the American Automatic Control Council in recognition of his outstanding contribution in the field of Automatic Control. He had served as an Associate Editor of the IEEE Transactions of Automatic Control, and a co-editor of the Journal of Economic Dynamics and Control, which he co-founded.
Professor Tse has done research in system and control engineering, economic dynamics and control, computer integrated systems to support fishery management policy decisions, management and control of manufacturing enterprise, and industrial competitive analysis and product development. Tse developed a framework for analyzing dynamic competitive strategy that would shape the formation of an ecosystem supporting a value proposition. Within such a framework, he developed dynamic strategies for firms entering an emerging market, latecomers entering a matured market, and firms managing transformation. Using this framework, he developed a new theory on the business transformation of a company and the economic transformation of a developing economy. He applied his theory to explain China’s rapid growth since 1978, changing from a production economy to an innovation economy. His current research is extending the theory to managing product success, managing inflection point disruptions, sustainable growth strategy in a dynamic changing environment, and industries’ strategy responding to geopolitics disruption. Over the years he has made valuable contributions in the field of engineering, economics, and business creation and expansion. He has published over 180 papers on his research activities.
From 2004- 2015, he co-directed various Stanford-China programs on regional industry and enterprise transformation that were attended by high level city officials from various cities in China and high level executives from Chinese enterprises. From 2007-2013, he co-directed a Stanford Financial Engineering Certificate Program in Hong Kong that upgrades the quality of managers and traders in the financial institutions in Hong Kong
He was a co-founder and a Board member of Advanced Decision System (ADS), a technology company with emphasis on AI and advanced decision tools. The company was found in 1979 and later acquired by Booz Allen and Hamilton in 1991. In 1988, Verity was spun off from ADS with AI search engine technology developed in ADS to provide enterprise search software. He was a Board member of Verity representing ADS before Verity went IPO in 1995. From 2007-2010, he was a Board member of KBC Fund Management Co., Ltd.
