School of Humanities and Sciences
Showing 1,701-1,720 of 1,948 Results
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Ayelet Voskoboynik
Assistant Professor (Research) of Biology
Current Research and Scholarly InterestsWe study the mechanisms by which animals differentiate between self and non-self, and how stem cells and immune cells coordinate to form tissues during development, regeneration, transplantation, and aging. By leveraging the natural stem cell-mediated development, regeneration, and chimerism in the colonial chordate Botryllus schlosseri, we investigate stem cell competition and the decline in regenerative capacity during aging.
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Jelena Vuckovic
Jensen Huang Professor of Global Leadership, Professor of Electrical Engineering and, by courtesy, of Applied Physics
Current Research and Scholarly InterestsJelena Vuckovic’s research interests are broadly in the areas of nanophotonics, quantum and nonlinear optics. Her lab develops semiconductor-based photonic chip-scale systems with goals to probe new regimes of light-matter interaction, as well as to enable platforms for future classical and quantum information processing technologies. She also works on transforming conventional photonics with the concept of inverse design, where optimal photonic devices are designed from scratch using computer algorithms with little to no human input. Her current projects include quantum and nonlinear optics, cavity QED, and quantum information processing with color centers in diamond and in silicon carbide, heterogeneously integrated chip-scale photonic systems, and on-chip laser driven particle accelerators.
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Robert Wagoner
Professor of Physics, Emeritus
Current Research and Scholarly InterestsProbes (accretion disks, ...) of black holes, sources and detectors of gravitational radiation, theories of gravitation, anthropic cosmological principle.
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Virginia Walbot
Professor of Biology, Emerita
Current Research and Scholarly InterestsOur current focus is on maize anther development to understand how cell fate is specified. We discovered that hypoxia triggers specification of the archesporial (pre-meiotic) cells, and that these cells secrete a small protein MAC1 that patterns the adjacent soma to differentiate as endothecial and secondary parietal cell types. We also discovered a novel class of small RNA: 21-nt and 24-nt phasiRNAs that are exceptionally abundant in anthers and exhibit strict spatiotemporal dynamics.
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Patrick Walsh
Ph.D. Student in Applied Physics, admitted Autumn 2025
BioPatrick graduated with honors from the University of Wisconsin-Madison in 2025 with a B.S. in Applied Math, Engineering, and Physics. He conducted his undergraduate research under Professor Mark Eriksson, where he studied Semiconductor Quantum Dot Qubits. His work focused on developing experimental techniques and numerical tools to automate gate-voltage calibration procedures for quantum dot devices. As an NSF Fellow and rotation student with the Bøttcher group at Stanford, Patrick is interested in using Josephson Junction Arrays to study a variety of problems in condensed matter, including vortex dynamics, quantum phase transitions, and highly correlated materials.
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Guenther Walther
John A. Overdeck Professor
BioGuenther Walther studied mathematics, economics, and computer science at the University of Karlsruhe in Germany and received his Ph.D. in Statistics from UC Berkeley in 1994.
His research has focused on statistical methodology for detection problems, shape-restricted inference, and mixture analysis, and on statistical problems in astrophysics and in flow cytometry.
He received a Terman fellowship, a NSF CAREER award, and the Distinguished Teaching Award of the Dean of Humanities and Sciences at Stanford. He has served on the editorial boards of the Journal of Computational and Graphical Statistics, the Journal of the Royal Statistical Society, the Annals of Statistics, the Annals of Applied Statistics, and Statistical Science. He was program co-chair of the 2006 Annual Meeting of the Institute of Mathematical Statistics and served on the executive committee of IMS from 1998 to 2012. -
Karen D. Wang
Affiliate, Physics
BioMy research is situated at the intersection of machine learning and human cognition. In my work, I apply learning analytics and data mining techniques to students’ interaction data in technology-based learning environments. The goal is to translate fine-grained behavioral data into meaningful evidence about students’ cognitive and metacognitive processes. These enhanced understandings of students’ mental processes and competencies are then used to guide the design of and evaluate instructional materials embedded in educational technology.
