Big Data: The Nobel Conference continues online

Mel Pardock – Staff Writer

On October 5 & 6 of 2021, Gustavus will be hosting the 57th annual Nobel Conference virtually. This year’s theme is Big Data REvolution, and it will look into how big data is changing our lives, alongside the challenges and opportunities this evolution will bring.
Big data is defined by the Oxford Dictionary as “extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.” Big Data impacts all of our lives in a variety of ways, such as personalized marketing, risk management, and social media algorithms.
“Big Data methods such as machine learning are used in almost every discipline to take advantage of all of the data that we and our devices generate. Medicine, public health, economics, you name it. This conference focuses primarily on the positive aspects of Big Data but we will definitely discuss some of the concerns such as privacy and bias”, conference co-chair Thomas LoFaro said.
The 57th conference will feature seven speakers, featuring professors of health, statistics, mathematics, bioethics, data science, and more, alongside university research chairs and regents professors. Each speaker has a biography listed on the Nobel Conference website.
“Every year a committee forms to plan the Nobel Conference that will happen in two years. We spend about the first semester and a half collecting recommendations for presenters, discussing them and thinking about how they will fit together to explore multiple layers of a topic. For this year’s conference, we wanted to explore the way big data is employed in a variety of fields, from criminal justice to health care”, conference director Lisa Heldke said.
These speakers give attendees much to look forward to. In addition to their own talks at the conference, there will be four panels in which the speakers will gather to discuss their presentations and thoughts on big data together.
“I think there are two things that I’m really excited about. First, is hearing about the use of Big Data in public health in general but epidemiology in particular. Secondly, I am interested in hearing about ‘interpretable machine learning.’ Once a machine learning (or artificial intelligence) algorithm has been trained to learn something, it is often quite difficult to understand how it is making the decisions it does,” LoFaro said.
If you have any questions about the conference or are interested in learning more, visit the conference’s website,, or contact co-chairs Thomas LoFaro or Karl Larson.

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