Data and analytics

Agri-food and health informatics is essential for understanding the complexity of the data that technology is delivering. The ability to utilize that data for design, and for identifying risks, resilience, and potential failures is a rich opportunity for design.
With the capacity for evaluating data, decision processes and creating strategic efficiencies in labor, production, processing, distribution become more rapid and better grounded. Artificial Intelligence and Machine Learning are the basis of such innovations.
The increased expectation for sharing data sets from federally funded projects means larger and more data resources are available, reducing the requirement for original field work for every research question, and leading to more applied research studies on evaluation and decisions and rapid guidance for stakeholders.
Affiliate faculty within the Data Analytics platform
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Bio ItemChi Ta , bio
data analytics | sustainability | energy | environment
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Bio ItemYuan Zeng , bio
molecular plant-pathogen interactions | epidemiology | environmental sensing | statistics | computational biology
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Bio ItemRobin White , bio
livestock | sustainability | sensors | robotics | data analytics
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Bio ItemElinor Benami , bio
remote sensing | environment | risk management | machine learning
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Bio ItemDurelle Scott , bio
water quality | water quantity | restoration | non-point source pollution
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Bio ItemSaied Mostaghimi , bio
environmental assessment and remediation | precision agriculture | systems modeling | water quality
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