Technological advances in hardware, storage, and software have increased scientists’ ability to find new and unique ways of generating and using data. This creates exciting new possibilities for conducting research that addresses the complex challenges of environmental contamination and ecological risk assessment. Through high-resolution data acquisition, data mining, and visualization techniques, scientists can better understand the fickle and fleeting nature of aquatic data and pollutant movement across boundaries.
In today's world, data-intensive science requires significant collaboration between environmental and computer scientists. This cooperation is becoming increasingly critical in finding more effective ways to research, discover and solve problems. The work done by our team in Research Focus Area 3 will facilitate these collaborations and support CREST CAChE researchers to better detect and understand the sources, transport, transformation and ecosystem responses to contaminants in South Florida's complex aquatic systems. This will ultimately allow us to provide the public and decision-makers with models of future scenarios, and predict future conditions under a changing landscape and climate. To learn more, read the full proposal for RFA 3 below.
The TeamShahin Vassigh, Lead: data visualization and education
Jose Eirin-Lopez, Lead: genetic and epigenetic adaptation
Marcus Cooke: biomonitoring genotoxin exposure
Quentin Felty: estrogen-mimicking endocrine disruptors
Mark Finlayson: artificial intelligence, natural language processing, and cognitive science
Michael Heithaus: large predator behavior and ecosystem impacts
Tao Li: data mining and machine learning
Assefa M. Melesse: eco-hydrological and geospatial modeling
Gary Rand: ecotoxicology and risk assessment
Shu-Ching Chen: multimedia data mining and analytics