School of Humanities and Sciences

Showing 1-20 of 22 Results

  • Jianghong Rao

    Jianghong Rao

    Professor of Radiology (Molecular Imaging Program at Stanford) and, by courtesy, of Chemistry

    Current Research and Scholarly InterestsProbe chemistry and nanotechnology for molecular imaging and diagnostics

  • Kristy Red-Horse

    Kristy Red-Horse

    Associate Professor of Biology

    Current Research and Scholarly InterestsCardiovascular developmental biology

  • Seung Yon Rhee

    Seung Yon Rhee

    Associate Professor (By Courtesy), Biology

    BioSeung Yon (Sue) Rhee is a Senior Staff Member of Plant Biology Department at Carnegie Institution for Science. Her group strives to uncover the molecular mechanisms underlying adaptive traits in the face of heat, drought, nutrient limitation, latitude and pests. Dr. Rhee’s group studies a variety of plants including models, orphan crops, medicinal and desert plants. More recently their work has involved studying a model nematode C. elegans, fungal pathogens, corals, and piexophilic bacterium. Her group employs computational modeling and targeted laboratory testing to study mechanisms of adaptation, functions of novel genes, organization and function of metabolic networks, and chemical and neuronal code of plant-animal interactions. Her group is also interested in developing translational research programs involving carbon sequestration by plants and biomass maximization under drought in bioenergy crops. Dr. Rhee received her B.A. in biology from Swarthmore College and a Ph.D. in biology from Stanford University. She has been an investigator at the Plant Biology Department of Carnegie Institution for Science since 1999.

  • Thomas Rogerson

    Thomas Rogerson

    Basic Life Research Scientist

    Current Research and Scholarly InterestsAs a postdoctoral research fellow in the laboratory of Mark Schnitzer I am utilizing chronic, in vivo, fluorescence calcium-imaging combined with chemo and optogenetic manipulations to determine the mechanisms by which neuronal circuits and the ensembles of cells within them enable the encoding and recall of context-dependent memories.

  • David Rogosa

    David Rogosa

    Associate Professor of Education and, by courtesy, of Biomedical Data Science and of Statistics

    Current Research and Scholarly InterestsStatistical issues in educational assessment; analysis of longitudinal data.

  • Joseph Romano

    Joseph Romano

    Professor of Statistics and of Economics

    Current Research and Scholarly InterestsWork in progress is described under "Projects"

  • 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

  • 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.