Jacobs Named Director of UMD Center for Machine Learning

David Jacobs, a professor of computer science with an appointment in the University of Maryland Institute for Advanced Computer Studies (UMIACS), was recently named director of the University of Maryland Center for Machine Learning for a three-year term, effective July 1, 2020.

Jacobs has served as interim director of the center since its launch in April of 2019. He oversees a vibrant research community of core faculty and graduate students focused on developing applications and technology for machine learning that involve computer vision, neural networks, optimization, robotics, 3D audio, and more.

Jacobs is intent on increasing the center’s activities on several fronts: research, education, and diversity. He is also committed to developing new partnerships both on and off campus.

“We see the center as a portal for machine learning at Maryland,” he says. “By reaching out to other faculty and increasing our external relationships, we’ll continue to build the strong intellectual and computational infrastructure needed to address scientific and societal challenges best solved by machine learning.”

A highlight of activities in the UMD Center for Machine Learning for the past year include:

Core faculty member Aravind Srinivasan is leading the computational foundations part of a $10M National Science Foundation (NSF) Expeditions in Computing project to develop strategies to thwart disease outbreaks. Key to this work, Srinivasan says, is the development of new machine learning algorithms that can interpret large amounts of data from multiple sources over multiple networks.

The center launched a Rising Stars in Machine Learning seminar series last fall, bringing up-and-coming female researchers to the UMD campus to present their work and interact with faculty and students. Faculty in the center, led by Soheil Feizi, are currently working on expanding the seminar series to include other underrepresented researchers.

Technology and financial leader Capital One, an inaugural partner in the center’s launch, provided a $125K gift-in-kind of a graphics processing unit (GPU) cluster that has 220 cores, four-plus terabytes of memory and 320 terabytes of storage. With additional support from UMIACS and the College of Computer, Mathematical, and Natural Sciences, the center is able to provide a robust computing environment for its faculty, students and visiting scholars.

Faculty in the center are receiving significant public recognition for their research and scholarship. This includes a story by The New Yorker featuring Tom Goldstein’s work on an “invisibility cloak;” Furong Huang’s research in using classical machine learning algorithms to better understand deep neural networks; and the robotics work by Pratap Tokekar—a recent addition to the center—highlighted in a video that was featured in the NSF’s multimedia gallery.

More news on the Center for Machine Learning can be read here. For the latest updates on the center’s activities, follow them on Twitter.