To help address the growing need for a larger workforce of health data analysts and technologists, Rensselaer Polytechnic Institute and the United Health Foundation are expanding access to health informatics educational opportunities and applied health data science research experiences through the Rensselaer Institute for Data Exploration and Application (IDEA).
Current research in computational geometry has two themes. The first 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.
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.
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 corresponding programming paradigms.
At the CogWorks Lab we are interested in basic and applied research in the area of immediate interactive behavior. On the basic side, we are working to understand the interplay of cognition, perception, and action in routine interactive behavior. These interests entail understanding top-down versus bottom-up control of behavior, the role of implicit versus explicit knowledge, internal versus external representations, and knowledge in-the-head versus knowledge in-the-world.
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 networks. Research also spans emerging areas like microarray data analysis, protein design, high dimensional indexing, database support, information integration, and data mining.
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.
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 massively parallel computing methods, 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 parallel adaptive unstructured mesh methods.
In order for robots to reach their full potential as productive members of society, they must become more autonomous, socially adept, and dexterous. Toward this end, the research in the Computer Science Robotics Laboratory is focused on three areas: grasping and manipulation, physical simulation, and planning and control for autonomous operation in unstructured environments.