Johns Hopkins launches institute aimed at understanding, improving big data analysis

November 2, 2017

 

Big Data

Johns Hopkins University will launch a new interdisciplinary institute aimed at developing the mathematical theories that will hasten the analysis of the massive amounts of data being used to study everything from the inner workings of the human cell to the structure of the universe.

The Johns Hopkins Mathematical Institute for Data Science, or MINDS, brings together a core group of 10 researchers and a dozen other faculty members working at the intersection of mathematics, statistics, and theoretical computer science. The group plans to establish the fundamental principles that make it possible to analyze and interpret massive amounts of high-dimensional, complex data.

René Vidal a professor of biomedical engineering and director of the Vision Dynamics and Learning Lab, has been named director of MINDS.

“MINDS will become the place at Johns Hopkins where you go if you have large data sets and need theory and algorithms to analyze them,” says Vidal, an expert in machine learning, computer vision, and biomedical imaging. “We will focus on the theoretical foundations—developing new mathematical and statistical methods and guaranteeing that these methods are correct.”

Vidal describes the mathematical quandary at the heart of artificial intelligence’s deep learning as a something of a “black box” that works not on theory, but on trial and error. Computer algorithms are making giant leaps in accuracy with tasks such as identifying a human face (think Facebook tagging), but these declines in error rates are not clearly understood because of the lack of an underlying theory, he says.

“But once you understand the inner workings of the mechanics, then you can make improvements in performance and robustness,” Vidal says. “That’s what we plan to do.”

Excerpted from The Hub.

 

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