The Center for Machine Learning launched in 2019 to unify and enhance the many machine learning activities underway at the University of Maryland. Faculty members from mathematics, chemistry, biology, physics, linguistics and computer science are developing applications and technology for machine learning, and the multidisciplinary center provides a central hub for them to collaborate and leverage shared resources.
"We want the center to be a focal point across the campus where faculty, students and visiting scholars can come to learn about the latest technologies and theoretical applications based in machine learning," said the center’s director, David Jacobs. Jacobs is a professor of computer science with a joint appointment in UMIACS.
Researchers involved with the center are developing new applications in computer vision, finance, natural language processing and other areas. They are also conducting research to advance machine learning theory and improve the technology behind machine learning and deep neural networks, which are modeled off networks in the brain and are capable of processing massive amounts of data.
"No one really knows why neural networks work as well as they do," Jacobs said. "We want to better understand the properties of deep learning and neural networks. We want to learn how to build better neural networks, train them better and understand their weaknesses."
Located in the Brendan Iribe Center for Computer Science and Engineering, the center leverages the powerful computational infrastructure of UMIACS, which provides computing resources as well as technical and administrative support. The College of Computer, Mathematical, and Natural Sciences provided initial funding for the center along with additional support from inaugural partner Capital One.
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This sidebar was published in the Spring 2020 issue of Odyssey magazine. To read other stories from that issue, please visit go.umd.edu/odyssey.