The CMS deparment includes a number of labs, specialized in various scientific fields, but working synergistically in collaborative projects.
Applied Geometry Lab
The Applied Geometry Lab at Caltech approaches computations involved in computer graphics and physical simulation from a geometric standpoint in order to provide numerical tools that intrinsically respect key defining properties like symmetries and invariants. In particular, we focus on discrete differential modeling, i.e., the development of differential, yet readily-discretizable foundations of computations, with a wide spectrum of applications from discrete geometry processing to solid and fluid mechanics. Learn more at: http://www.geometry.caltech.edu.
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. Learn more at: http://www.async.caltech.edu.
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.Learn more at: http://www.vision.caltech.edu/html-files/overview.html.
DNA and Natural Algorithms Group
Our group is interested in biomolecular computation: how systems of biomolecules, such as DNA and enzymes, can process information and carry out algorithms. Our main task is to investigate how synthetic biochemical systems can be designed to carry out algorithms and compute; what models of computation arise from biochemical processes and how they can be programmed; and how to "compile" abstract descriptions of biomolecular algorithms down to specific synthetic DNA sequences that implement the desired computation in the laboratory. While our theoretical studies are wide-ranging, our experimental efforts focus on coaxing DNA to perform algorithmic tricks. Learn more at: http://www.dna.caltech.edu/
The research of the Caltech 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. Learn more at: http://www.gg.caltech.edu/.
The Infospheres group carries out research on theory, design methodology, and prototype development of sense and respond (S&R) systems. The lab applies theory to a number of projects in formal methods and practical applications in distributed information, collaboration over the Web, Java, and the Internet. Learn more at: http://www.infospheres.caltech.edu.↑ top
Laboratory for Reliable Software
The Laboratory for Reliable Software (LaRS) is a Center of Excellence at JPL in the Systems and Software Division. The Lab's mission is to achieve long term improvements in the reliability of JPL's mission critical software systems. To do so, it pursues a project-driven research program that targets the application of both new and existing formal verification techniques to mission software. The group members focus on identifying key vulnerabilities in mission software and try to find meaningful remedies for them. LaRS projects can target any part of the software life-cycle, from requirements capture and analysis, to high-level and low-level software design, coding, testing, deployment and mission operations. LaRS members have strong connections with colleagues at leading Universities and research labs worldwide, and specifically also with researchers at other NASA centers, such as NASA Ames Research, Kennedy Space Center, Johnson Space Center, Langley, Marshall, and Goddard. Learn more at: http://lars-lab.jpl.nasa.gov/.
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. Learn more at: http://www.work.caltech.edu
Multi-Res Modeling Group
Under the direction of Prof. Peter Schröder, our research touches on many areas of computer graphics with a focus on Digital Geometry Processing and, more recently, Discrete Differential Geometry. Our work focuses on solid mathematical foundations and robust numerical algorithms, with an eye on generality and uniformity, scalability, simple data structures and algorithms, and conciseness of representation. Our main goal is to design representations and algorithms to address issues of robust modeling, simulation, and rendering in highly complex computer graphics environments. Learn more at: http://www.multires.caltech.edu
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. Learn more at: http://www.paradise.caltech.edu
Our work is focused on engineering small conditional RNAs (scRNAs) that interact and change conformation to execute molecular logic in vitro, in situ, and in vivo. This research program exploits the programmable chemistry of nucleic acid base-pairing. We seek to engineer small conditional RNAs that function as programmable molecular instruments within intact biological specimens, or as conditional chemotherapies, selectively activating in diseased cells, while leaving normal cells untouched.
To enable the systematic design of small conditional RNAs that execute diverse dynamic functions, we are also working to develop mathematically rigorous, physically sound, computationally efficient algorithms for programming molecular function. Our long-term goal is to develop a compiler for molecular programming that takes as input a modular conceptual device design and provides as output the sequences of scRNAs that interact to implement the desired function. Learn more at: http://www.piercelab.caltech.edu/
Rigorous Systems Research Group (RSRG)
The Rigorous Systems Research Group (RSRG, pronounced "resurge") studies the design of computer systems, but it's not your ordinary systems group. RSRG is distinguished by its rigorous/analytic approach to design. The group develops new theory, uses theoretical results to provide new design tools and methodologies, puts these new design tools and methodologies into practice, and develops new theory motivated by practice, thus closing the loop.
The research process of RSRG is centered around three themes, the combination of which distinguish RSRG from most other CS systems groups: Theory is important: Everybody in the group develops new theoretical results that inform system design and performance analysis; Get your hands dirty: Everybody in the group builds, or uses measurements from, systems and prototypes; Be interdisciplinary : Everybody in the group uses ideas from disciplines outside computer science---such as operations research, economics, and control theory---or develops systems that are used in varied disciplines such as space exploration or control of power grids. Learn more at: http://www.cs.caltech.edu/research/rsrg/.
Robotics and Bioengineering Group
Our research group covers both Robotics and BioEngineering: our research is divided between traditional robotics research, and collaborations with neuroscientists to develop technology for paralyzed nervous systems. Topics in robotics include the design of rovers for extreme planetary terrains, robot motion planning in dynamic cluttered environments, ultra-wide band radar tracking of humans, activity recognition, grasping and mobile manipulation; topics in NeuroEngineering include high density epidural spinal stimulation and neural prosthetics---the goal being a direct brain interface that enables a human, via the use of surgically implanted electrode arrays and associated computer decoding algorithms, to control external electromechanical devices by pure thought alone. Learn more at: http://robotics.caltech.edu/.
Theory of Computation
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). Learn more at: http://www.cs.caltech.edu/research/theory/