School of Humanities and Sciences
Showing 1,301-1,400 of 1,948 Results
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Xiaoliang Qi
Professor of Physics
BioMy current research interest is the interplay of quantum entanglement, quantum gravity and quantum chaos. The characterization of quantum information and quantum entanglement has provided novel understanding to space-time geometry, and relate the dynamics of chaotic many-body systems to the dynamics of space-time, i.e. quantum gravity theory. Based on recent progress in holographic duality (also known as AdS/CFT), my goal is to use tools such as tensor networks and solvable models to provide more microscopic understanding to the emergent space-time geometry from quantum states and quantum dynamics.
I am also interested in topological states and topological phenomena in condensed matter systems.
You can find my recent research topics in some talks online:
http://online.kitp.ucsb.edu/online/chord18/opgrowth/
https://www.youtube.com/watch?v=__9VBaLfC6Y&t=42s
http://online.kitp.ucsb.edu/online/qinfo_c17/qi/ -
Stephen Quake
Lee Otterson Professor in the School of Engineering and Professor of Bioengineering, of Applied Physics and, by courtesy, of Physics
Current Research and Scholarly InterestsSingle molecule biophysics, precision force measurement, micro and nano fabrication with soft materials, integrated microfluidics and large scale biological automation.
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Krishna Raghavan
Ph.D. Student in Chemistry, admitted Autumn 2024
BioKrishna is originally from the Detroit area of Michigan, and completed his undergraduate studies in biological chemistry and chemistry at the University of Chicago. He is currently a second-year PhD student concentrating in biophysical chemistry, in the lab of Prof. Bianxiao Cui.
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Srinivas Raghu
Professor of Physics
BioI am interested in the emergent behavior of quantum condensed matter systems. Some recent research topics include non-Fermi liquids, quantum criticality, statistical mechanics of strongly interacting and disordered quantum systems, physics of the half-filled Landau level, quantum Hall to insulator transitions, superconductor-metal-insulator transitions, and the phenomenology of quantum materials.
Past contributions that I'm particularly proud of include the co-founding of the subject of topological photonics (with Duncan Haldane), scaling theories of non-Fermi liquid metals (with Shamit Kachru and Gonzalo Torroba), Euclidean lattice descriptions of Chern-Simons matter theories and their dualities in 2+1 dimensions (with Jing-Yuan Chen and Jun Ho Son), and 'dual' perspectives of quantum Hall transitions (with Prashant Kumar and Michael Mulligan). -
Alok Ranjan
Physical Science Research Scientist
BioAccomplished Research Scientist with a rich history (6-8 years) of spearheading cutting-edge research projects. Proficient in synthesizing and analyzing new compounds with therapeutic potential. Experienced in utilizing both structure and property-based strategies to identify promising drug candidates. Led multidisciplinary teams to innovate solutions, enhanced drug discovery efficiency by integrating advanced computational techniques. Committed to continuous learning and staying well-informed of the latest trends in medicinal chemistry and drug design.
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Adithi Rao
Life Science Rsch Prof 2, Biology
Current Role at StanfordResearch Professional at the Laboratory of Organismal Biology, Gilbert Hall
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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
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Kristy Red-Horse
Professor of Biology
Current Research and Scholarly InterestsCardiovascular developmental biology
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Leon Reilly
Undergraduate, Mathematics
Undergraduate, PhilosophyBiohttps://leonreilly.io/
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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.
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Joseph Romano
Professor of Statistics and of Economics
Current Research and Scholarly InterestsWork in progress is described under "Projects"
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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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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. -
Silvia Russi
Research and Development Scientist and Engineer, Stanford Synchrotron Radiation Lightsource Laboratory (SSRL)
Current Role at StanfordBeamline Scientist, Structural Molecular Biology (SMB), Stanford Synchrotron Radiation Lightsource (SSRL), SLAC National Accelerator Laboratory, Stanford University
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Anders Rydstrom
Postdoctoral Scholar, Biology
BioAnders Rydstrom is a Postdoctoral Scholar with the Natural Capital Project and is investigating the links between exposure to nature areas and health. His research primarily focuses on conducting randomized controlled trials (RCTs) with uses of multimodal data sources such as accelerometers, ecological momentary assessments, behavioral outcomes and biometric health data. Anders received his Ph.D. in psychology and neuroscience from Karolinska Institute in Stockholm, Sweden, where he analyzed heterogeneity of treatment effects in lifestyle oriented RCT’s for prevention of Alzheimer’s Disease and cognitive impairment. He has also conducted research within cognitive training and emotion regulation. He holds an M.Sc. in psychology from Lund University, Lund, Sweden and has also clinical experience from working as a licensed healthcare psychologist in Scandinavia.
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Chiara Sabatti
Professor of Biomedical Data Science and of Statistics
On Leave from 10/01/2025 To 03/27/2026Current Research and Scholarly InterestsStatistical models and reasoning are key to our understanding of the genetic basis of human traits. Modern high-throughput technology presents us with new opportunities and challenges. We develop statistical approaches for high dimensional data in the attempt of improving our understanding of the molecular basis of health related traits.
