School of Engineering
Showing 1-10 of 13 Results
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Daniel J O'Shea
Research Engineer, Bioengineering
Current Research and Scholarly InterestsI study the neural mechanisms that control movement, and more broadly, how neural populations spanning interconnected brain regions perform the distributed computations that drive skilled behavior. I develop experimental and computational tools to understand the neural population dynamics that establish speed and dexterity.
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Allison Okamura
Richard W. Weiland Professor in the School of Engineering and Professor, by courtesy, of Computer Science
Current Research and Scholarly InterestsMy research focuses on developing the principles and tools needed to realize advanced robotic and human-machine systems capable of physical interaction. Application areas include surgery, simulation and training, rehabilitation, prosthetics, neuromechanics, exploration of hazardous and remote environments (e.g. space), design, and education.
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Kunle Olukotun
Cadence Design Systems Professor, Professor of Electrical Engineering and of Computer Science
BioKunle Olukotun is the Cadence Design Professor of Electrical Engineering and Computer Science at Stanford University. Olukotun is a pioneer in multicore processor design and the leader of the Stanford Hydra chip multiprocessor (CMP) research project. He founded Afara Websystems to develop high-throughput, low-power multicore processors for server systems. The Afara multi-core processor, called Niagara, was acquired by Sun Microsystems and now powers Oracle's SPARC-based servers. In 2017, Olukotun co-founded SambaNova Systems, a Machine Learning and Artificial Intelligence company, and continues to lead as their Chief Technologist.
Olukotun is the Director of the Pervasive Parallel Lab and a member of the Data Analytics tor What's Next (DAWN) Lab, developing infrastructure for usable machine learning. He is a member of the National Academy of Engineering, an ACM Fellow, and an IEEE Fellow for contributions to multiprocessors on a chip design and the commercialization of this technology. He also received the Harry H. Goode Memorial Award.
Olukotun received his Ph.D. in Computer Engineering from The University of Michigan. -
Leonard Ortolano
UPS Foundation Professor of Civil Engineering in Urban and Regional Planning, Emeritus
BioOrtolano is concerned with environmental and water resources policy and planning. His research stresses environmental policy implementation in developing countries and the role of non-governmental organizations in environmental management. His recent interests center on corporate environmental management.
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Brad Osgood
Professor of Electrical Engineering and, by courtesy, in Education
BioOsgood is a mathematician by training and applies techniques from analysis and geometry to various engineering problems. He is interested in problems in imaging, pattern recognition, and signal processing.
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Khalid Osman
Assistant Professor of Civil and Environmental Engineering and Center Fellow, by courtesy, at the Woods Institute for the Environment
BioKhalid Osman joined the department as an Assistant Professor of Civil and Environmental Engineering in autumn of 2022. His research spans the use of mixed quantitative-qualitative methods to assess public perceptions of water infrastructure, water conservation efforts, and the management of existing infrastructure systems to meet the needs of those being served by the systems. He currently is focused on the operationalization of equity in water sector infrastructure, conceptualizing equity in decentralized water and sanitation systems, water affordability, and stakeholder-community engagement in sustainable civil infrastructure systems for achieving environmental justice.
Khalid was the holder of a Bill and Melinda Gates Millennium Scholars Graduate Fellowship and also a Ford Foundation Predoctoral Fellowship. -
Zihao Ou
Physical Science Research Scientist
BioMy research interests have been focusing on how individual building blocks come together resulting in complex functions which are hard to predict, if possible, from the individual identities. Similar to a digital screen displaying a movie, the complicated pattern and story can hardly be interpreted from the dynamic traces of a single pixel. Specifically, I have been studying the general topic of self-assembly and non-equilibrium behaviors in soft matter systems, using both experimental and simulation tools.
I obtained my B.S. degree in physics from University of Science and Technology of China (USTC) in 2015. In my undergraduate research, I tried to use computer simulation to study multiple systems in Prof. Zhonghuai Hou’s group, such as the Viscek model for self-propelled particles. In 2014, I visited Oxford University to study the phase behaviors of active nematics using Lattice-Boltzmann method in Prof. Julia M. Yeomans' group. In 2020, I obtained my Ph.D. degree in Materials Science and Engineering at University of Illinois at Urbana-Champaign (UIUC) under the supervision of Prof. Qian Chen. During my Ph.D. research, we illustrated the nonclassical crystallization pathway of nanoparticles (Nat. Mater., 19, 450–455, 2020) and supracrystal growth kinetics (Nat. Commun., 11, 4555, 2020) using liquid-phase TEM. I also studied other nonequilibrium behaviors in novel colloidal systems, such as shape transformation of metal-organic framework crystals during chemical etching (ACS Appl. Mater. Interfaces, 10, 48, 40990–40995, 2018), application of ferromagnetic colloids in inductor design (Science Adv., 6, 3, eaay4508, 2020) and electron transport in redox-active colloids.
In August 2020, I joined Prof. Guosong Hong’s group at the materials science and engineering department at Stanford University to develop novel nanomaterials that can interact with neurons at the subcellular level. Armed with the knowledge of nanotechnology and theoretical modeling, we are extending the tools that can be used to investigate the challenging questions in neuroscience. -
Nicholas Ouellette
Professor of Civil and Environmental Engineering
Current Research and Scholarly InterestsThe Environmental Complexity Lab studies self-organization in a variety of complex systems, ranging from turbulent fluid flows to granular materials to collective motion in animal groups. In all cases, we aim to characterize the macroscopic behavior, understand its origin in the microscopic dynamics, and ultimately harness it for engineering applications. Most of our projects are experimental, though we also use numerical simulation and mathematical modeling when appropriate. We specialize in high-speed, detailed imaging and statistical analysis.
Our current research includes studies of turbulence in two and three dimensions, with a focus on coherent structures and the geometry of turbulence; the transport of inertial, anisotropic, and active particles in turbulence; the erosion of granular beds by fluid flows and subsequent sediment transport; quantitative measurements of collective behavior in insect swarms and bird flocks; the stability of ocean ecosystems; neural signal processing; and uncovering the natural, self-organized spatiotemporal scales in urban systems.
