The American Association for the Advancement of Science has elected Peter Fox, data scientist and professor at Rensselaer Polytechnic Institute, as a Fellow of the society, in recognition of his “distinguished, innovative, and sustained fundamental contributions in Earth and space science informatics and data science research, education, and service.”
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.