IMA Announces New Data Science Consortium

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The IMA is pleased to announce a $2 million initiative in partnership with Minnesota-based companies Target and Cargill to create a consortium that will address the mathematical foundations of data science and its applications. The IMA will leverage its experience in developing sustainable research communities in nascent fields of the mathematical sciences, building connections between academia, industry, and applied mathematics, and bringing together researchers from different disciplines to address problems arising in science, technology, and society.

Data science touches upon many different disciplines though its underpinnings are mathematical and algorithmic. With the creation of a new data science consortium, the IMA is well-positioned to address the gap between data science practice and its foundations. The industrial collaboration also provides a broader variety of problems that will allow academia to expand the boundaries of data science.

Each academic semester will feature a three-month program that focuses on a basic research theme of common interest to academia and the consortium’s corporate partners. The first program begins in spring 2018 and covers forecasting from complex data, including spatio-temporal and networked systems. Programs will include two workshops organized by leaders in the field and invite experts for long-term visits at the IMA to conduct research related to the theme and interact with Minnesota’s data science community.


The first workshop of the program is called Frontiers in Forecasting, held February 21-23, 2018, and will bring together experts and early-career researchers to discuss state-of-the-art forecasting methods for data-driven industry applications and scientific discovery. The second workshop, entitled Forecasting from Complexity, will take place April 23-27, 2018 and discuss methods for analyzing data from complex and dynamic processes to improve our ability to forecast future events and characterize the associated uncertainties.