Data Mining Research in Climate Science, Earth Science, and Bioinformatics
This group has three major research tracks:
- Understanding Climate Change Using Data-Driven Approaches: Data-driven approaches that have been highly successful in other scientific disciplines hold significant potential for application in environmental sciences. This Expeditions project addresses key challenges in the science of climate change by developing methods that take advantage of the wealth of climate and ecosystem data available from satellite and ground-based sensors, the observational record for atmospheric, oceanic, and terrestrial processes, and physics-based climate model simulations.
- Monitoring Land Cover Change at Global Scale: The key focus of this project is to develop new computer science methods and tools that enable effective monitoring of various land cover changes happening on the earth's surface. This group has analyzed various land cover changes such as forest fires, deforestation, insect infestation in forests, urbanization, agricultural changes, and monitoring of water resources. The group has made significant improvements in monitoring forest fires at global scale. Currently, the major focus has been on monitoring change in water bodies across the globe using remote sensing datasets.
- Data Mining for Biomedical Informatics: This group is focused on developing novel data mining and machine learning techniques to analyze a wide variety of biomedical datasets. Some of their latest areas of focus have been on analyzing electronic health record (EHR) data, brain scan data, and next-generation sequencing data. They collaborate with an interdisciplinary set of researchers in fields such as nursing, psychology, cell biology, and cancer genetics.
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