School of Engineering
Showing 1-10 of 13 Results
Professor of Mechanical Engineering and, 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.
Cadence Design Systems Professor and Professor of Electrical Engineering
BioKunle Olukotun is the Cadence Design Systems Professor in the School of Engineering and Professor of Electrical Engineering and Computer Science at Stanford University. Olukotun is well known as a pioneer in multicore processor design and the leader of the Stanford Hydra chip multiprocessor (CMP) research project. Olukotun founded Afara Websystems to develop high-throughput, low-power multicore processors for server systems. The Afara multicore processor, called Niagara, was acquired by Sun Microsystems. Niagara derived processors now power all Oracle SPARC-based servers. Olukotun currently directs the Stanford Pervasive Parallelism Lab (PPL), which seeks to proliferate the use of heterogeneous parallelism in all application areas using Domain Specific Languages (DSLs).
Assistant Professor of Energy Resources Engineering and, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsModeling, control and optimization of dynamic systems;
Model-based control in advanced propulsion systems;
Energy management control and optimization in HEVs and PHEVs;
Energy storage systems- Li-ion and PbA batteries, Supercapacitors;
Battery aging modeling, state of health estimation and life prediction for control;
Damage degradation modeling in interconnected systems
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.
Professor of Electrical Engineering and, by courtesy, of 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.
Research Engineer, Chemical Engineering
BioMy interests include partial differential equations, stochastic calculus and numerical algorithms with applications to fluid/statistical mechanics and finance. During my PhD, I developed shape optimization algorithms for polymeric materials; as a research engineer, I developed parallel algorithms to compute Brownian motion of particles correlated through a fluid media. I currently work in a major bank as a quantitative analyst.
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.