School of Engineering
Showing 4,901-5,000 of 6,994 Results
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Juan Rivas-Davila
Associate Professor of Electrical Engineering and Senior Fellow at the Precourt Institute for Energy
Current Research and Scholarly InterestsModern applications demand power capabilities beyond what is presently achievable. High performance systems need high power density and bandwidth that are difficult to achieve.
Power density can be improved with better semiconductors and passive componets, and by reducing the energy storage requirements of the system. By dramatically increasing switching frequency it is possible to reduce size of power converters. I'm interested in high performance/frequency circuits switching >10 MHz. -
Eric Roberts
The Charles Simonyi Professor in the School of Engineering, Emeritus
BioFrom 1990-2002, Roberts served as associate chair and director of undergraduate studies for the Computer Science Department before being appointed as Senior Associate Dean in the School of Engineering and later moving on to become Faculty Director for Interdisciplinary Science Education in the office of the VPUE.
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Stephen Rock
Professor of Aeronautics and Astronautics, Emeritus
BioProfessor Rock's research interests include the application of advanced control and modeling techniques for robotic and vehicle systems (aerospace and underwater). He directs the Aerospace Robotics Laboratory in which students are involved in experimental programs designed to extend the state-of-the-art in robotic control. Areas of emphasis include planning and navigation techniques (GPS and vision-based) for autonomous vehicles; aerodynamic modeling and control for aggressive flight systems; underwater remotely-operated vehicle control; precision end-point control of manipulators in the presence of flexibility and uncertainty; and cooperative control of multiple manipulators and multiple robots. Professor Rock teaches several courses in dynamics and control.
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Justin S. Rogers
Research Oceanographer, Civil and Environmental Engineering
Staff, Civil and Environmental EngineeringBioPh.D. Civil & Environmental Engineering, Stanford University, 2016
M.S. Civil & Environmental Engineering, University of Wisconsin-Madison, 2006
B.S. Civil Engineering (Minor in Chemistry), University of Arizona, 2004
Research interests:
-Coastal resilience, risk, sea level rise, extreme events, compound hazards
-Impact of climate change on human and natural systems in coastal and nearshore environments
-Core model development for coastal applications, storm surge, tropical cyclones, flood risk, bottom boundary layers, turbulence, and multiscale physics.
I leverage the power of cloud computing, HPC systems and modern code frameworks, and adapt multiple analysis methods including dynamical models, machine learning, statistical methods, and field observations. -
Heidi Roizen
Adjunct Lecturer, Management Science and Engineering
BioHeidi Roizen is a venture capitalist, corporate director and former technology CEO/entrepreneur. Today, Heidi is a partner at leading venture firm Threshold Ventures and serves as a board member for private companies Upside Foods and Polar in the Threshold portfolio. She is currently also an independent corporate director for Planet (NYSE:PL). Heidi is also an Adjunct Lecturer at Stanford University and leads Stanford’s Threshold Venture Fellows Program in the Management Science and Engineering department. Heidi also serves on the advisory councils of the Stanford Institute for Human-Centered Artificial Intelligence (HAI) and Stanford Technology Ventures (STVP). She started her career as co-founder of software company T/Maker and served as its CEO for over a dozen years until its acquisition by Deluxe Corporation. After a year as VP of Worldwide Developer Relations at Apple, Heidi then became a venture capitalist in 1999. She has undergraduate and MBA degrees from Stanford and is the proud mother of two kids and two rescue dogs.
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Luca Rosalia
Postdoctoral Scholar, Bioengineering
BioLuca Rosalia received his bachelor’s and master’s degrees in Biomedical Engineering from the University of Glasgow (UK). During his studies, he visited the National University of Singapore and the University of Cambridge, where he gained his first exposure to the fields of soft robotics and tissue biomechanics. He pursued doctoral studies in the Health Sciences and Technology (HST) Ph.D. program of Harvard University and Massachusetts Institute of Technology in the lab of Ellen Roche and he's currently at Stanford University as a Postdoctoral Scholar in Bioengineering in the Skylar-Scott lab.
His doctoral work primarily focused on high-fidelity and patient-specific soft robotic preclinical models of valvular heart disease, congenital defects, and heart failure with preserved ejection fraction. Luca leveraged these platforms for the testing and development of medical devices through several partnerships with industry. During his studies, he also worked as an R&D engineer in the Structural Heart division of Abbott Laboratories on the development of transcatheter aortic valve replacements (TAVR). He also gained clinical experience at the Veterans Affairs Medical Center in Boston and at Boston Children's Hospital. In the Skylar-Scott lab, Luca will be working on whole-heart bioprinting. -
Noah Rosenberg
Stanford Professor of Population Genetics and Society
Current Research and Scholarly InterestsHuman evolutionary genetics, mathematical models in evolution and genetics, mathematical phylogenetics, statistical and computational genetics, theoretical population genetics
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Mendel Rosenblum
Cheriton Family Professor and Professor of Electrical Engineering
On Leave from 10/01/2023 To 06/30/2024Current Research and Scholarly InterestsNext generation data centers
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Bernard Roth
Professor of Mechanical Engineering, Emeritus
BioRoth is one of the founders of the Hasso Plattner Institute of Design at Stanford (the d.school) and is active in its development: currently, he serves as Academic Director. His design interests include organizing and presenting workshops on creativity, group interactions, and the problem solving process. Formerly he researched the kinematics, dynamics, control, and design of computer controlled mechanical devices. In kinematics, he studied the mathematical theory of rigid body motions and its application to the design of machines.
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Grant M. Rotskoff
Assistant Professor of Chemistry
BioGrant Rotskoff studies the nonequilibrium dynamics of living matter with a particular focus on self-organization from the molecular to the cellular scale. His work involves developing theoretical and computational tools that can probe and predict the properties of physical systems driven away from equilibrium. Recently, he has focused on characterizing and designing physically accurate machine learning techniques for biophysical modeling. Prior to his current position, Grant was a James S. McDonnell Fellow working at the Courant Institute of Mathematical Sciences at New York University. He completed his Ph.D. at the University of California, Berkeley in the Biophysics graduate group supported by an NSF Graduate Research Fellowship. His thesis, which was advised by Phillip Geissler and Gavin Crooks, developed theoretical tools for understanding nonequilibrium control of the small, fluctuating systems, such as those encountered in molecular biophysics. He also worked on coarsegrained models of the hydrophobic effect and self-assembly. Grant received an S.B. in Mathematics from the University of Chicago, where he became interested in biophysics as an undergraduate while working on free energy methods for large-scale molecular dynamics simulations.
Research Summary
My research focuses on theoretical and computational approaches to "mesoscale" biophysics. Many of the cellular phenomena that we consider the hallmarks of living systems occur at the scale of hundreds or thousands of proteins. Processes like the self-assembly of organelle-sized structures, the dynamics of cell division, and the transduction of signals from the environment to the machinery of the cell are not macroscopic phenomena—they are the result of a fluctuating, nonequilibrium dynamics. Experimentally probing mesoscale systems remains extremely difficult, though it is continuing to benefit from advances in cryo-electron microscopy and super-resolution imaging, among many other techniques. Predictive and explanatory models that resolve the essential physics at these intermediate scales have the power to both aid and enrich the understanding we are presently deriving from these experimental developments.
Major parts of my research include:
1. Dynamics of mesoscale biophysical assembly and response.— Biophysical processes involve chemical gradients and time-dependent external signals. These inherently nonequilibrium stimuli drive supermolecular organization within the cell. We develop models of active assembly processes and protein-membrane interactions as a foundation for the broad goal of characterizing the properties of nonequilibrium biomaterials.
2. Machine learning and dimensionality reduction for physical models.— Machine learning techniques are rapidly becoming a central statistical tool in all domains of scientific research. We apply machine learning techniques to sampling problems that arise in computational chemistry and develop approaches for systematically coarse-graining physical models. Recently, we have also been exploring reinforcement learning in the context of nonequilibrium control problems.
3. Methods for nonequilibrium simulation, optimization, and control.— We lack well-established theoretical frameworks for describing nonequilibrium states, even seemingly simple situations in which there are chemical or thermal gradients. Additionally, there are limited tools for predicting the response of nonequilibrium systems to external perturbations, even when the perturbations are small. Both of these problems pose key technical challenges for a theory of active biomaterials. We work on optimal control, nonequilibrium statistical mechanics, and simulation methodology, with a particular interest in developing techniques for importance sampling configurations from nonequilibrium ensembles.
