Joshi to lead CMU’s AI-EDGE team

The U.S. National Science Foundation has announced the establishment of 11 new NSF National Artificial Intelligence Research Institutes. Focused on AI-based technologies, these new institutes will advance technology in fields ranging from agriculture to engineering.

Among the 11 new institutes is the AI Institute for Future Edge Networks and Distributed Intelligence (AI-EDGE). Led by The Ohio State University, Carnegie Mellon’s Gauri Joshi, assistant professor of electrical and computer engineering, will manage the CMU team of researchers that includes Ameet Talwalkar, assistant professor in the Machine Learning Department.

“The overarching research mission of the AI-EDGE Institute will be to design next-generation intelligent edge networks that are efficient, reliable, robust, and secure,” says Joshi. “The focus will be on edge networks ​​that consist of diverse components including mobile phones, sensors, robots, self-driving cars that are connected to backhaul networks, and data centers.”

The focus will be on edge networks that consist of diverse components including mobile phones, sensors, robots, self-driving cars that are connected to backhaul networks, and data centers.

Gauri Joshi, Assistant Professor, Electrical and Computer Engineering

AI-EDGE will develop new AI tools and techniques to ensure that wireless edge networks are self-healing and self-optimized. These networks will make AI more efficient, interactive, and privacy-preserving for applications in sectors such as intelligent transportation, remote health care, distributed robotics, and smart aerospace.

Carnegie Mellon University is a globally recognized leader in machine learning, artificial intelligence, and networked computing systems. The confluence of these areas puts the team in a unique position to make a lasting impact on next-generation AI edge networks. Joshi and Talwalkar are leaders in the emerging field of federated learning, a framework that trains machine learning models using data collected by edge devices.

Joshi’s research vision is to democratize machine learning by enabling it to seamlessly scale to a network of resource-constrained nodes. She is designing distributed training and inference algorithms that are communication-efficient and can handle heterogeneity in computation and data. Joshi recently developed a new course on algorithms for distributed machine learning, which is one of the very few courses on distributed optimization and federated learning. She is also passionate about outreach and mentorship to women pursuing STEM careers.

Joshi recently received the NSF CAREER award and the ACM SIGMETRICS 2020 Best Paper Award for her work.

AI-EDGE will create a research, education, knowledge transfer, and workforce development environment that will help establish U.S. leadership in next-generation edge networks and distributed AI for many decades to come.

Read the official NSF press release here.

The AI Institute for Future Edge Networks and Distributed Intelligence is led by The Ohio State University’s Ness Shroff, professor of electrical and computer engineering and computer science and engineering. The core team consists of 30 scientists from 11 collaborating institutions, three Department of Defense research labs, and four global companies. The collaborating institutions include: The Ohio State University, Carnegie Mellon University, Northeastern University, Purdue University, University 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.