School of Engineering
Showing 171-180 of 382 Results
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Peter K. Kitanidis
Professor of Civil and Environmental Engineering
BioKitanidis develops methods for the solution of interpolation and inverse problems utilizing observations and mathematical models of flow and transport. He studies dilution and mixing of soluble substances in heterogeneous geologic formations, issues of scale in mass transport in heterogeneous porous media, and techniques to speed up the decay of pollutants in situ. He also develops methods for hydrologic forecasting and the optimization of sampling and control strategies.
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Fredrik Kjolstad
Assistant Professor of Computer Science
BioFredrik Kjolstad is an Assistant Professor in Computer Science at Stanford University. He works on topics in compilers, programming models, and systems, with an emphasis on compiler techniques that make high-level languages portable. He has received the NSF CAREER Award, the MIT EECS Sprowls PhD Thesis Award in Computer Science, the Tau Beta Phi 2024 Teaching Honor Roll, the Google ML and Systems Junior Faculty Awards, and several distinguished paper awards.
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Perry Klebahn
Adjunct Professor, d.school
Instructor, Stanford Engineering Center for Global and Online EducationBioWhen it comes to startups, corporations and executive leadership, Perry’s seen just about everything. He's a seasoned entrepreneur, product designer, chief executive and co-founding member of the d.school faculty with over 20 years of experience. He also loves math, motorcycles and making things. Perry brought two out of three of those interests to bear when he created a new category of sportswear by way of a high-performance shoe — a snowshoe — for his product design master’s thesis. He went on to found the Atlas Snowshoe Company, which remains the leader in snowshoe design and technology. Perry sold Atlas and became the head of Sales and Marketing for the clothing brand, Patagonia in 2000. He then went on to be named the CEO of the iconic bag company, Timbuk2 in 2007. Both opportunities gave him extensive experience in brand turn-around, design and innovation. Despite his years running startups and corporations, Perry’s true calling is teaching. He leverages the breadth and depth of his experience as he pushes his students to bring rigor and precision to their fast-paced design work. His students often tell him that, while they were intimidated by him during the course, they're grateful for the pressure he placed on them to exceed their own expectations. Perry is a founding teaching team member for the d.school’s startup gauntlet class, Launchpad, the innovation leadership course, d.leadership and the week-long executive education intensive, Bootcamp. He is also on the teaching teams for the personal development course, Designer in Society and the organizational change course, d.org. In every class, Perry guides his students to look back in order to discover what to do next and works from the unshakeable belief that it’s always possible to see a problem differently.
Perry is an Adjunct Professor and Director of Executive Education at the d.school. He holds a B.A. in Physics from Wesleyan University (1988) and a Master’s degree in Product Design from Stanford University (1991). -
Mykel Kochenderfer
Associate Professor of Aeronautics and Astronautics, Senior Fellow at the Stanford Institute for Human-Centered AI and Associate Professor, by courtesy, of Computer Science
BioMykel Kochenderfer is Associate Professor of Aeronautics and Astronautics at Stanford University. Prior to joining the faculty, he was at MIT Lincoln Laboratory where he worked on airspace modeling and aircraft collision avoidance, with his early work leading to the establishment of the ACAS X program. He received a Ph.D. from the University of Edinburgh and B.S. and M.S. degrees in computer science from Stanford University. Prof. Kochenderfer is the director of the Stanford Intelligent Systems Laboratory (SISL), conducting research on advanced algorithms and analytical methods for the design of robust decision making systems. Of particular interest are systems for air traffic control, unmanned aircraft, and other aerospace applications where decisions must be made in uncertain, dynamic environments while maintaining safety and efficiency. Research at SISL focuses on efficient computational methods for deriving optimal decision strategies from high-dimensional, probabilistic problem representations. He is an author of "Decision Making under Uncertainty: Theory and Application" (2015), "Algorithms for Optimization" (2019), and "Algorithms for Decision Making" (2022), all from MIT Press. He is a third generation pilot.
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Christoforos Kozyrakis
Leonard Bosack and Sandy K. Lerner Professor of Engineering and Professor of Computer Science
BioChristos Kozyrakis is the Leonard Bosack and Sandy K. Lerner Professor of Engineering and a Professor of Electrical Engineering and Computer Science at Stanford University. His primary research areas are computer architecture and computer systems. His current work focuses on cloud computing, systems for machine learning, and machine learning for systems.
Christos holds a BS degree from the University of Crete and a PhD degree from the University of California at Berkeley. He is a fellow of the ACM and the IEEE. He has received the ACM SIGARCH Maurice Wilkes Award, the ISCA Influential Paper Award, the NSF Career Award, the Okawa Foundation Research Grant, and faculty awards by IBM, Microsoft, and Google. -
Ellen Kuhl
Catherine Holman Johnson Director of Stanford Bio-X, Walter B Reinhold Professor in the School of Engineering, Professor of Mechanical Engineering and, by courtesy, of Bioengineering
Current Research and Scholarly Interestscomputaitonal simulation of brain development, cortical folding, computational simulation of cardiac disease, heart failure, left ventricular remodeling, electrophysiology, excitation-contraction coupling, computer-guided surgical planning, patient-specific simulation
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Ching-Yao Lai
Assistant Professor of Geophysics
BioMy group attacks fundamental questions in fluid dynamics and geophysics by integrating mathematical and machine-learned models with observational data. We use our findings to address challenges facing the world, such as advancing our scientific knowledge of ice dynamics under climate change. The length scale of the systems we are interested in varies broadly from a few microns to thousands of kilometers, because the governing physical principles are often universal across a range of length and time scales. We use mathematical models, simulations, and machine learning to study the complex interactions between fluids and elasticity and their interfacial dynamics, such as multiphase flows, flows in deformable structures, and cracks. We extend our findings to tackle emerging topics in climate science and geophysics, such as understand the missing physics that governs the flow of ice sheets in a warming climate. We welcome collaborations across disciplinary lines, from geophysics, engineering, physics, applied math to computer science, since we believe combining expertise and methodologies across fields is crucial for new discoveries.
