Michael Ferris

Michael Ferris enjoys mathematical puzzles, and he uses data science to solve puzzles with real-world applications. Through his research, he aims to produce better decisions and outcomes for a wide range of environmental and societal challenges, from reducing pollution caused by dairy farm manure to increasing renewable energy use and delivering COVID-19 vaccines fairly.

Michael supports decision makers by developing mathematical models to allocate limited resources like vaccine doses and clean energy. In the case of energy planning, for example, models can describe energy supply and demand, and movement from sources to end users. However, these models are complicated by uncertainties about future energy demand and renewable technologies such as wind, solar and hydro. Data science gives Ferris tools to address the complex interplay between different kinds of data, allowing him to address uncertainty in his models.

In Michael’s view, data science enhances the value of data by providing insights about what is happening in complex, interacting systems, so we can predict future possibilities. Data science is deeply intertwined with uncertainty and increases our understanding of it to produce better outcomes for society.

“One hopes that the state of Wisconsin continues to understand the value of having a great university to help with its scientific and computational outputs, as I think this can have a great influence on the positioning of Wisconsin as a leading entity in the data science revolution.”