Princeton’s Sam Wang applies data analysis to the cerebellum, gerrymandering

Sam Wang is professor of molecular biology and neuroscience at Princeton University, where his research focuses on the cerebellum and its role in cognition and social thought processes. He employs neural imaging and data analytics to search for clues to the causes of autism, a major concern of his laboratory.

“When faced with complex data, the difficulty is to extract an understandable simple meaning from a large data set,” Wang said, as reported by Michael Hotchkiss of the Princeton Office of Communications. “My general approach to data analysis, to the extent possible in neuroscience, is to take all the observations we make in the lab and try to come up with some relatively simple fact that can be stated about the data.”

If you’re not a neuroscientist, perhaps you’re familiar with Wang in his role as founder of the Princeton Election Consortium website, where he applies his expertise in data analytics to predicting the outcomes of national elections.

In that role, Wang misjudged the outcome of the 2012 elections to the U.S. House of Representatives. “He rightly predicted that Democratic candidates would get more votes than Republican candidates in House races across the country,” Hotchkiss reports. “He also foretold that Democrats would regain control of the House. That’s where he was wrong.”

Hotchkiss quotes Wang as saying, “The incorrect prediction bothered me. I wanted to figure out why I was wrong.” His examination led to the publication in June of the article “Three Tests for Practical Evaluation of Partisan Gerrymandering” in the Stanford Law Review.

You can read the complete profile of Wang here. As Wang notes, “It may be the only time you will ever find the cerebellum and gerrymandering mentioned in the same article.”