Hulya Seferoglu joins edge network research team at new NSF AI Institute

by Andrea Poet | Posted on July 30, 2021

The National Science Foundation is expanding its research in artificial intelligence, including edge computing, with 11 new NSF National Artificial Intelligence Research Institutes, focused on a variety of technologies. Associate Professor Hulya Seferoglu, whose research includes the design, analysis, and implementation of network protocols and algorithms, is part of the newly established AI Institute for Future Edge Networks and Distributed Intelligence, or AI-EDGE.

According to the NSF, AI-EDGE will involve scholars from Carnegie Mellon University, Northeastern University, Purdue University, University of Wisconsin-Madison, University of Michigan, University of Texas-Austin, University of Washington, University of Massachusetts-Amherst, University of Illinois-Urbana-Champaign and University of Illinois Chicago. It also will work with industry partners, including AT&T, IBM, Microsoft, and Qualcomm, and with the Air Force Research Lab, Army Research Lab, and Naval Research Lab to translate the research so that it is widely adopted. The AI-EDGE Institute will be led by an Ohio State team and will receive $20 million over five years.

Seferoglu will work with colleagues from other institutions to lead the push for equity and inclusion across the NSF’s AI Research Institutes. They hope to build on existing efforts at each participating university while developing new opportunities to help bring talented undergrads from diverse backgrounds into graduate-level study. Also, Seferoglu and her group will conduct research at the intersection of distributed machine learning and network protocol and algorithm design.

The NSF says this expansion builds on an initial round of seven institutes, funded in 2020, and is focused on AI-based technologies that will bring about a range of advances: helping older adults to lead more independent lives and improving the quality of their care, transforming AI into a more accessible “plug-and-play” technology, improving agriculture and food supply chains, enhancing adult online learning, and supporting underrepresented students in STEM education at all levels to improve equity and representation in AI research.