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  Projects in Intelligent Data Understanding and Uncertain Inference
  Polishing: Enhancing Data Quality by Repairing Imperfections
  Software Agents and Knowledge Discovery and Data Mining Research for Complex System Safety, Health, and Process Monitoring
  Development and Testing of Data Mining Algorithms for Earth Observation and Other NASA Applications
  Automated Examination of Reflectance Spectra
  Algorithms for Determining Genetic Regulatory Networks

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  Research :: Intelligent Data Understanding and Uncertain Inference

Experimental and observational studies generate large amounts of data. However, without well-designed algorithms, computers do not analyze the data with sufficient efficiency.

Improving algorithms for data analysis requires finding efficient ways to produce simple intuitive rules for classifying objects, work on pre-processing data to reduce measurement errors, epistemic principles for making inferences based on statistical data and general background knowledge, and work on methods for combining expert knowledge with new data to provide insight into the causal processes behind the data.

Improved data processing is critical in situations with limited computing power, such as space exploration, as well as in analysis of complex systems, such as climate modeling or gene regulation.