School of Engineering
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Adjunct Professor, Mechanical Engineering
BioGary has a strong research focus on sensors designed for use in Advanced Driver Assistance Systems (ADAS), Automated Driving (AD) and manned spaceflight Aerospace applications.
Gary began his career focused on sensors while working for Lockheed Space Operations at Kennedy Space Center, FL from 1984-1992 as an electrical flight-systems engineer. His work responsibilities included installation and calibration/test of sensor arrays, (accelerometers, gyroscopes, pressure, strain-gauges, temperature, hazardous-gas, etc.), located on the Space Shuttle Orbiter, External tank, and Solid Rocket Boosters. Gary worked in Motorola's Sensor Products Division (1993-2005) located in Tempe, AZ, where he was focused on sensor based ASIC and Transducer R&D product development activities (inertial, pressure, chemical, etc.), including Ford's first automotive airbag accelerometer. From 2005 to 2007, he led MEMS research activities and taught multiple graduate level analog and digital ASIC design courses as a professor in the Electrical Engineering Department at Arizona State University, Tempe, AZ. From 2007-2009 he served as VP of Engineering at Memsic Inc., located in Andover, MA. Gary worked at Bosch from 2009-2015 as Director of the MEMS Advanced Development Group (ADG) at the Research and Technology Center (RTC) located in Palo Alto, CA. Gary was the Advanced Engineering Global Engineering Director at Delphi Electronics and Safety (E&S) from 2015 to 2018.
Gary is currently an Adjunct Professor at Stanford University in the Mechanical Engineering Department and is the course instructor for graduate course ME429, "Commercial MEMS Design" from 2011 to present. Gary is also currently a Sr. Design Engineer working on manned spaceflight rocket propulsion systems at Northrop Grumman Innovation Systems located at Kennedy Space Center, FL.
Dr. O'Brien earned his BSEE from the Florida Institute of Technology, an MSEE from the Georgia Institute of Technology, and a Ph.D. in Electrical Engineering from the University of Michigan
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).
UPS Foundation Professor of Civil Engineering in Urban and Regional Planning
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.
Engr Res Assoc, Chemical Engineering
BioMy research interests include computational mathematics, parallel algorithms, soft matter and stochastic calculus. During my PhD, using polymer field theory and level set methods, I developed shape optimization algorithms for predicting the phases of polymeric materials with a free surface. I recently developed parallel algorithms on distributed memory architecture for Accelerated Stokesian Dynamics (ASD) to simulate large-scale stochastic particle systems correlated through hydrodynamic interactions. I currently try to embed modern machine learning techniques to exploit the data generated by ASD simulations. I am also interested in stochastic calculus theory and applications.
Associate 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.