School of Engineering


Showing 1-27 of 27 Results

  • Priyanka Raina

    Priyanka Raina

    Assistant Professor of Electrical Engineering and, by courtesy, of Computer Science

    Current Research and Scholarly InterestsFor Priyanka's research please visit her group research page at https://stanfordaccelerate.github.io

  • Ram Rajagopal

    Ram Rajagopal

    Associate Professor of Civil and Environmental Engineering and of Electrical Engineering

    BioRam Rajagopal is an Associate Professor of Civil and Environmental Engineering at Stanford University, where he directs the Stanford Sustainable Systems Lab (S3L), focused on large-scale monitoring, data analytics and stochastic control for infrastructure networks, in particular, power networks. His current research interests in power systems are in the integration of renewables, smart distribution systems, and demand-side data analytics.

    He holds a Ph.D. in Electrical Engineering and Computer Sciences and an M.A. in Statistics, both from the University of California Berkeley, Masters in Electrical and Computer Engineering from University of Texas, Austin and Bachelors in Electrical Engineering from the Federal University of Rio de Janeiro. He is a recipient of the NSF CAREER Award, Powell Foundation Fellowship, Berkeley Regents Fellowship and the Makhoul Conjecture Challenge award. He holds more than 30 patents and several best paper awards from his work and has advised or founded various companies in the fields of sensor networks, power systems, and data analytics.

  • Christopher Re

    Christopher Re

    Associate Professor of Computer Science

    Current Research and Scholarly InterestsAlgorithms, systems, and theory for the next generation of data processing and data analytics systems.

  • Martin Reinhard

    Martin Reinhard

    Professor (Research) of Civil and Environmental Engineering, Emeritus

    BioReinhard studies the fate of organic substances in the subsurface environment and develops technologies for the remediation of groundwater contaminated with chlorinated and non-chlorinated hydrocarbon compounds. His research is concerned with mechanistic aspects of chemical and biological transformation reactions in soils, natural waters, and treatment systems.

  • Juan Rivas-Davila

    Juan Rivas-Davila

    Associate Professor of Electrical Engineering

    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

    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.

  • Stephen Rock

    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.

  • Noah Rosenberg

    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

  • Mendel Rosenblum

    Mendel Rosenblum

    Cheriton Family Professor and Professor of Electrical Engineering

    Current Research and Scholarly InterestsNext generation data centers

  • Bernard Roth

    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.

  • Grant M. Rotskoff

    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.