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This page lists each group with a summary of research. For more on each group please visit the corresponding web sites linked at each description.
Asynchronous VLSI | Computer Graphics Group |Computational Vision Group | Implementation of Computation | Infospheres | Learning Systems Group | Multi-Res Modeling Group | Networking Laboratory | (Paradise) Parallel and Distributed Systems Group | Theory of Computation
The
asynchronous VLSI group, under Prof. Alain J. Martin,
studies techniques for the design of high-performance and low power asynchronous
digital circuits. Past projects have included the first asynchronous
microprocessor in silicon and gallium-arsenide, and an asynchronous digital
filter. Our current project is the design of an asynchronous MIPS processor.
http://www.async.caltech.edu
The
research of the Caltech Computer Graphics Group primarily focuses on the
mathematical foundations of computer graphics. The group's long term goals
are to develop and explore new approaches to modeling, rendering, simulation
and scientific visualization. This effort is highly connected to our work
on human/computer interaction. New methods are needed to increase modeling
fidelity, "fluency," and interactivity. This is accomplished
using mathematical principles from differential geometry, constrained
optimization, integral equations and piecewise differential equations,
as well as physical principles such as the mechanics of solids and the
physics of light. The approach of our research team, Profs. Arvo, Barr,
and Schröder, is unique in its mathematical rigor. The common theme
of our work has been an emphasis both on correct underlying mathematical
foundations and on careful realization in efficient, robust algorithms.
http://www.gg.caltech.edu/
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Computational
Vision Group
The Computational
Vision laboratory studies the computational aspects of vision. We are
interested both in building machines that can see, and in understanding
the mechanisms of biological vision. Our approach is both analytical and
experimental, with insight from geometry, optics, signal processing, functional
analysis, and through computational simulations and psychophysical tests.
http://www.vision.caltech.edu/html-files/overview.html
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Under
the direction of Prof. André DeHon studies of how we physically
implement computations are taking place. Our efforts span from algorithms
and problem descriptions, through compute models, architectures, and runtime
systems, and down to physical substrates, including work on design mapping
between these levels. We attempt to systematically understand the design
space for programmable computing devices and the impact that both substrate
costs and mapping technology have on that design space. Currently, we
are focusing on Programmable System-on-a-Chip designs, interconnect, and
architectures for early molecular electronic devices. http://www.cs.caltech.edu/research/ic/
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The
Infospheres project researches compositional ways of obtaining high
confidence in dynamically-reconfigurable scalable distributed systems.
The group seeks to further its vision of a worldwide pool of millions
of objects (or agents) much like the pool of documents on the worldwide
web today. We are exploring infrastructures that allow objects to
find other objects with specific attributes, negotiate protocols
with them, and then set up compositional structures for collaborative
computation. An important aspect of our research is high-confidence
in adaptive systems. The group develops systems and also explores
the theory of distributed computing. Our theoretical work is based
on temporal logic for reasoning about correctness, and probability
theory for reasoning about performance.
http://www.infospheres.caltech.edu
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Learning
Systems group
The
Learning Systems group works on the theory, algorithms, and applications
of automated learning. We are committed to the understanding of the fundamental
concepts of automated learning, and to the development of real-life systems
that utilize learning to achieve state of the art performance. Our group
has pioneered the use of hints in learning. We have developed special
expertise in learning from very noisy data, which led to our activities
in Computational Finance. Computational finance is a relatively new field,
that explores computational and algorithmic methods to solve some of the
problems in the field of finance. We are interested in forecasting and
arbitrage, calibration of financial models, pricing of financial instruments,
portfolio optimization, and analytics for risk management. http://www.work.caltech.edu
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Under the direction of Prof. Peter Schršder the goal is the exploration
of multiresolution representations and algorithms to address issues of
robust modeling, simulation, and rendering in highly complex computer
graphics environments. http://www.multires.caltech.edu
Professor
Steven Low leads the group as it conducts research to understand, analyze,
control, optimize, simulate, and prototype network systems and protocols,
and networked computing. We are working on resource allocation and QoS
provisioning in Internet and wireless networks, and developing, with members
of the Lee Center for
Advanced Networking, a theory of complex networks. http://netlab.caltech.edu
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This
research group is focusing on a number of fundamental issues related to
the design of novel algorithms, protocols and architectures that enable
efficient fault-tolerant parallel and distributed computing for scientific
and commercial applications. This research program is a blend of basic
research and experimental systems activities, creating a balance between
theory and practice. The experimental activities are centered in the laboratory
for fault-tolerant parallel and distributed computing, which includes
a cluster of powerful workstations all connected via communication hubs
consisting of high-speed interconnects. The scope of the research program
consists of the following interrelated projects: RAIN (Reliable Array
of Independent Nodes), SNOW (Stable Network Of Webservers) and Protein
Networks. You can find the links to the projects in my group's web page.
http://www.paradise.caltech.edu
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What problems are computationally tractable? How is the answer to this question affected by the use of randomness as a resource? Or even more importantly -- by the fact that we live in a quantum mechanical world? What mathematics do we need to understand and develop in order to answer such questions? What happens when several computational agents interact -- how do they convey information to each other, hide information from each other, or combine their data or computational resources? In pursuing these questions, research in Theory of Computation at Caltech focuses on Algorithms (particularly randomized algorithms); Communication Protocols (with a focus on resilience to channel noise and network disruptions); Combinatorics (especially extremal combinatorics); Discrete Probability (random processes on trees and other graphs; inequalities); Coding and Information Theory (especially for interactive and distributed computations); and Quantum Computation (quantum algorithms, computational aspects of proposed physical realizations, quantum information theory). http://www.cs.caltech.edu/research/theory/
Asynchronous VLSI | Computer Graphics Group |Computational Vision group | Implementation of Computation | Infospheres | Multi-Res Modeling Group | Networking Laboratory | (Paradise) Parallel and Distributed Systems Group | Theory of Computation
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