Kerry J. Vahala
Ted and Ginger Jenkins Professor of Information Science and Technology and Applied Physics; Executive Officer for Applied Physics and Materials Science
Professor Vahala studies science and applications relating to high-Q optical microcavities. His research group has pioneered a class of devices that attain Q factors of nearly 1 billion in a compact size. They are using these devices to study optical parametric oscillators, frequency microcombs, high-coherence Brillouin lasers, reference cavities, optical-based microwave sources, and optomechanical oscillators.
P. P. Vaidyanathan
Kiyo and Eiko Tomiyasu Professor of Electrical Engineering
Sparse arrays for signal processing, compressive sensing and sparse reconstruction, spectrum sensing and applications in cognitive radio, filter banks, transform domain techniques for signal analysis, radar signal processing, and data driven signal processing.
Professor of Computing and Mathematical Sciences
Thomas Vidick's research is situated at the interface of theoretical computer science, quantum information and cryptography. He is interested in using complexity theory as a lens to approach fundamental problems in quantum computing. He has investigated the role of entanglement in multi-prover interactive proof systems and obtained the first substantial computational hardness results on the power of entangled provers. He has made important contributions to the field of device-independent cryptography, where the property of entanglement monogamy plays a key role. His work also demonstrates that insights from quantum information theory can be productively transferred to yield novel perspectives on fundamental techniques in theoretical computer science such as semidefinite programming and approximation algorithms.
Bren Professor of Medical Engineering and Electrical Engineering
Professor Wang’s research focuses on biomedical imaging. In particular, his lab has developed photoacoustic imaging that allows peering noninvasively into biological tissues. Compared to conventional optical microscopy, his techniques have increased the penetration by nearly two orders of magnitude, breaking through the optical diffusion limit. The Wang lab has invented or discovered functional photoacoustic tomography, 3D photoacoustic microscopy, optical-resolution photoacoustic microscopy, photoacoustic Doppler effect, photoacoustic reporter gene imaging, microwave-induced thermoacoustic tomography, universal photoacoustic reconstruction algorithm, time-reversed ultrasonically encoded optical focusing, and compressed ultrafast photography (world’s fastest camera capable of 10 trillion frames per second). Combining rich optical contrast and scalable ultrasonic resolution, photoacoustic imaging is the only modality capable of providing multiscale high-resolution structural, functional, metabolic, and molecular imaging of organelles, cells, tissues, and organs as well as small-animal organisms in vivo. Broad applications include early-cancer detection, surgical guidance, and brain imaging. For example, it can help surgeons effectively remove breast cancer lumps, reducing the need for follow-up surgeries. Professor Wang’s Monte Carlo model of photon transport in scattering media is used worldwide as a standard tool.
Vice President and Director of the Jet Propulsion Laboratory; Professor of Aerospace and Geophysics
Paul O. Wennberg
R. Stanton Avery Professor of Atmospheric Chemistry and Environmental Science and Engineering; Executive Officer for Environmental Science and Engineering; Director, Ronald and Maxine Linde Center for Global Environmental Science
Paul Wennberg studies the composition of the atmosphere of Earth and other planets. He is trained as a physical chemist and most of his investigations begin with atmospheric observations made by his research group in the laboratory or in the field. A hierarchy of models are used to study these observations. His group studies the carbon cycle, photochemistry, and air quality.
Professor of Computing and Mathematical Sciences; Executive Officer for Computing and Mathematical Sciences; Director, Information Science and Technology
Adam Wierman's research interests center around resource allocation and scheduling decisions in computer systems and services. More specifically, his work focuses both on developing analytic techniques in stochastic modeling, optimization, machine learning, and game theory, and applying these techniques to application domains such as energy-efficient computing, the cloud, the smart grid, and social networks.
Professor of Computer Science, Computation and Neural Systems, and Bioengineering
Professor Winfree's research involves theoretical and experimental aspects of molecular programming. Models of computation are developed that incorporate essential features of molecular folding, molecular self-assembly, biochemical circuits, and molecular robotics. These models are studied to determine their expressiveness for programming molecular-level tasks including decision-making, memory, behavior, and morphogenesis. Methods for compiling abstract molecular programs into actual molecules are developed and tested in the laboratory.
Thomas G. Myers Professor of Electrical Engineering, Bioengineering, and Medical Engineering
The research of the Biophotonics Laboratory, led by Professor Changhuei Yang, is focused on the development of novel tools that combine optics and microfluidics to tackle diagnostic and measurement problems in biology and medicine. His main research areas are ePetri, Fourier Ptychographic microscopy, and time-reversal optical focusing.
Martin and Eileen Summerfield Professor of Applied Physics and Electrical Engineering
Professor Amnon Yariv's research focuses on the theoretical and technological underpinning of optical communication. Present projects include: new types of semiconductor lasers, optical phase-lock systems and coherent photonics, hybrid Si/III-V devices for lasers, detectors and modulation, "Slow" light propagation in artificial periodic dielectric waveguides.
Assistant Professor of Computing and Mathematical Sciences
Yisong Yue's research interests lie primarily in the theory and application of statistical machine learning. He is particularly interested in developing novel methods for structured prediction, spatiotemporal reasoning, adaptive learning systems, and learning with humans in the loop. In the past, his research has been applied to information retrieval, content recommendation, text classification, learning from rich user interfaces, analyzing implicit human feedback, data-driven animation, sports analytics, policy learning in robotics, and adaptive routing and allocation problems.