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All Research Groups
Bioinformatics is the science of managing, retrieving, analyzing, and interpreting biological data. Research is being carried out on topics such as sequence assembly, protein and RNA structure prediction, sequence/structure/motifs, comparative genomics, and the gene regulatory network. Research also spans emerging areas like microarray data analysis, high dimensional indexing, database support, information integration, and data mining. Faculty: Chris Bystroff, Sanmay Das, Malik Magdon-Ismail, Lee Newberg, Bulent Yener, Mohammed Zaki. Computational Geometry Current research in computational geometry concentrates on algorithms for the reconstruction of smooth geometric objects from their samples. Problems of interest include characterizing the conditions on sampling density, which allow a curve to be reconstructed from its samples. The reconstruction is homeomorphic and sufficiently close to the original and the algorithms developed to achieve the reconstruction. Also involved are the dependence of such algorithms on the dimension of the embedding space, related algorithms for the reconstruction of surfaces and manifolds, and finding the most concise representation of a manifold in terms of its samples. A second research track focuses on applications of computational geometry, particularly in robotic motion planning. Faculty: Barbara Cutler, Wm. Randolph Franklin, Daniel Freedman, I. Volkan Isler, Charles Stewart. Computational Science and Engineering Students and faculty members work on computational approaches and algorithms to solve large-scale problems that arise in natural science and engineering. Current research includes adaptive methods for solving partial differential equations, multiscale computations, scientific software libraries, algorithms for medical imaging and tomography, high-performance matrix algorithms, computational biology, and adaptive software for high-performance computation over dynamic parallel and distributed environments. Faculty: David Isaacson, Ken Jansen, Frank Luk, Malik Magdon-Ismail, Mark Shephard, Boleslaw Szymanski, Carlos Varela. The faculty and students in the Computer Graphics Research Group are interested in a wide variety of rendering, geometry, simulation, and visualization problems motivated by computer games, special effects in movies, architectural design & pre-visualization, and many other exciting applications. We study topics including physically-based digital sculpting, efficient high-quality photo-realistic rendering, new data representations and algorithms, and the use of modern graphics hardware for interactive applications. Faculty: Barbara Cutler, Wm. Randolph Franklin. Computer vision and biomedical image analysis research in the Department of Computer Science covers a wide range of topics. Developing algorithms for registration and change detection, especially in the diagnosis and treatment of diseases of the human retina, is the largest current project; a related project studies the theory and application of robust estimation techniques in computer vision. A second research area focuses on the tracking and segmentation of objects, both in two- and three-dimensional images, using model-based algorithms. The techniques developed are general and may be used in a variety of computer vision tasks; the applications pursued at RPI are mainly focused on biomedical problems, such image-guided radiation therapy. A third track involves the development of stochastic models for the interpretation of video data, for example traffic video. Faculty: Daniel Freedman, I. Volkan Isler, Charles Stewart. Data Science: Data Mining; Machine and Computational Learning; Algorithms for Massive Data Sets This research area deals with the theoretical and applied aspects of automated information extraction (knowledge discovery) from data. For large data sets, emphasis is placed on developing efficient, scalable, and parallel algorithms for various data mining techniques in addition to the data management itself. Examples include association rules, classification, clustering, and sequence mining. For small data sets, the emphasis is on robust computational learning systems (supervised, unsupervised and reinforcement) and their theoretical properties. Application areas include combinatorial optimization, computational biology (bioinformatics, computational genomics), web mining, geographic information systems and computational finance. Faculty: Sanmay Das, Petros Drineas, Mark Goldberg, Malik Magdon-Ismail. Mohammed J. Zaki. Database Systems This research area deals with the efficient and effective methods for storing, querying and maintaining data from possibly disparate and heterogeneous resources. Data is used in many different applications from scientific data sets, sensor data, images, video and audio to hypertext documents, and data on stock market behavior. Research focuses on methods for caching data, querying large and distributed databases and supporting applications such as computer-aided design and manufacturing and collaborative engineering. Faculty: Sibel Adali, Martin Hardwick, David Spooner. Logic-Based Artificial Intelligence (RAIR Lab) Researchers in the RAIR Lab design and build intelligent agents, software, robots, etc. on the basis of formal logic. R&D has been and is sponsored by NSF, ARDA/DTO, AFOSR, etc. PhD students need to have some background in logic, AI, and relevant programming paradigms. Faculty: Selmer Bringsjord. Pervasive Computing and Networking Pervasive computing foresees a world in the not-distant future in which computer systems are embedded in everything: from personal digital assistants to implanted biological devices, to bridge-monitoring systems, and to teams of robots sent into a collapsed building to locate survivors. Untethered - wireless - communication is constant and, in many cases, so automated that human intervention is unneeded. Wireless, broadband community systems inexpensively bring people together for virtual town meetings, video doctor-patient conferences, and on-line business transactions. Computers in automobiles share information on congestion, quickly computing alternate routes. The promises are immense, but the challenges are formidable. The CS faculty cover the broad areas of pervasive networking and computing. Researchers investigate computer networks and their protocols, with a focus on wireless and sensor networks through the International Technology Alliance, a new 10-year research consortium led by the IBM Research Division and funded jointly by the US and UK Governments with participation of the leading researchers in the world. The focus is on sensor information processing and delivery, improvement of the quality of information obtained from sensor networks and adaptation of sensor networks to the dynamically changing user demands. Another area of activity is the security of computers, networks, and sensors. Secruity concerns are quickly becoming a significant barrier to the wide-spread acceptance of pervasive computing. The research tackles such issues as trust in Internet communications, identity of groups on the Internet, cryptographic and systemic challenges in sensor networks. Finally, in the area of high-performance pervasive computing, the focus is on computational environments in which task allocation, migration, and fault tolerance are supported automatically and on application of such environments to computations relevant to different scientific disciplines. Faculty: Chris Carothers, I. Volkan Isler, Bolek Szymanski, Carlos Varela, Bulent Yener. Programming Languages and Software Engineering The Programming Languages and Software Engineering research group investigates programming models, languages, concepts, methodologies, and tools to enable the development of correct, efficient, reliable, and maintainable software. Faculty: Ana Milanova, Dave Musser, Carlos Varela.
The goal of our research in robotics is to make the dream of personal robotic assistants a reality. Toward this end, we are engaged in research in the areas of (1) dexterous manipulation, (2) pursuit-evasion, (3) multi-robot coordination, and (4) human-robot collaboration. Dexterous manipulation is important because currently robots are able to sense various important aspects of the world around them, but they have great difficulty performing physical work. Robots cannot fulfill their potential until they can perform common manipulation tasks (such as making a bed or repairing a tile floor) that currently only humans can. Pursuit-evasion is important to efficient monitoring of the world around us. In particular, this area of research combines traditional robotics topics with some from computer vision. Multi-robot coordination enables a group of robots to perform tasks that individual robots will not be able to do. Developing coordination and control strategies is fundamental to this goal. Finally, human-robot collaboration is important to enabling personal robot assistants to work safely in unstructured environments with humans. In all of these areas, we are making research contributions of both theoretical and applied nature.
Faculty: I. Volkan Isler, Jeff Trinkle. Researchers in the security group focus on security problems at the systems level including discoverng hidden networks in social networks; network camouflaging; and privacy protection in data ming systems. Faculty: Mark Goldberg, Mukkai Krishnamoorthy, Malik Magdon-Ismail, Boleslaw Szymanski, Bulent Yener, Wei Zhao. Theory of Computation provides the foundation needed for effective applications. The theory group at Rensselaer's Computer Science Department brings together researchers in many areas of Computer Science to develop novel approaches and solutions to problems in information technology. Our research is characterized by close collaboration with researchers in diverse application areas, such as networking; bioinformatics; visualization; pattern recognition, physics and astronomy; digital library, data mining; and experimental algorithmics. Faculty:
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