Advanced Analytics Challenges

With the digital transformation in business and academia, the demand for advanced data analytics is increasing. LISH partners with foundations, government agencies, and research labs to access data analytics solutions through the crowd. Problems range from algorithm optimization to improving prediction: aligning data to objectives and turning data into knowledge, methodology, and applications.

EPA Cyanobacteria Predictive Modeling and Mobile App Challenge

The goal of this series of challenges, conducted from August 2013 to January 2015, was to predict the locations and times that the cyanobacteria bloom to occur. Algae are natural components of marine and freshwater flora performing many roles that... Read more about EPA Cyanobacteria Predictive Modeling and Mobile App Challenge

EPA ToxCast Predication Challenge

The goal of this 2014 challenge series was to develop a model, based on data provided by the U.S. Environmental Protection Agency, to quantitatively predict a chemical’s systemic Lowest Effect Level (LEL) in a traditional animal toxicity study. The systemic LEL is the lowest dose that shows adverse effects in these animal toxicity tests.... Read more about EPA ToxCast Predication Challenge

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Advanced Analytics Challenges

EPA Cyanobacteria Predictive Modeling and Mobile App Challenge

EPA ToxCast Predication Challenge

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