UT Researchers in Electrical Engineering and Computer Science Receive NSF CAREER Awards - University of Tennessee, Knoxville

Two researchers at the University of Tennessee, Knoxville, have received National Science Foundation CAREER awards for their work in superconducting logic systems and interactive human-centered computing. Their projects will address the challenge of scaling quantum computing and put artificial intelligence to work in Appalachian communities. Ahmedullah Aziz and Sai Swaminathan, both faculty in the Min H. Kao Department of Electrical Engineering and Computer Science in UT’s Tickle College of Engineering, received the awards through the NSF’s Faculty Early Career Development Program. The program, known as CAREER, recognizes and supports early-career faculty who have the potential to serve as academic role models in research and education, benefiting their organizations and the nation. “We are very proud of this year’s awardees,” said Deb Crawford, vice chancellor for research, innovation and economic development. “Their work will drive major breakthroughs and motivate students to share in the excitement and rewards of discovery. The impact will be felt across Tennessee and the nation.” Ahmedullah Aziz: Superconducting logic for future computing Aziz will receive $550,000 over five years to develop the fundamentals of a new generation of superconducting electronics — exceptionally fast energy-efficient circuits that can meet the demands of high-performance computing and serve as controllers for quantum computers that run in ultra-cold conditions. The work includes a reimagination of superconducting logic systems. Conventional logic systems use semiconductor transistors, which operate at room temperature, to enable computers to carry out calculations and make decisions. Superconducting logic systems are a form of computing hardware that process, route and store digital information using superconducting devices, which operate at ultra-low temperatures. They’re faster and use very little energy, but they currently lack important functionalities. Ahmedullah Aziz “My project focuses on making superconducting logic systems more functional, programmable and scalable, with better ‘control knobs’ and built-in memory,” Aziz said. His research group will develop predictive device models, design and evaluate new circuits and larger computing architectures, and fabricate and test prototypes to validate the underlying concepts. The resulting technologies will help tackle the rising energy demand of artificial intelligence infrastructure, and the superconducting logic systems will support the development of highly efficient larger-scale quantum computers by bringing more control, processing and memory functions into the cryogenic environment. “This award, and the opportunities to solve these challenges, would not be possible without the guidance, encouragement and support of my colleagues, mentors, family and students,” Aziz said. In turn, he is providing new opportunities to graduate and undergraduate students. “This funding will support a complete research pipeline. Just as importantly, it will support students who carry out the work,” he said. Aziz also plans to translate certain project elements into hands-on activities for high school students and teachers, allowing them to explore superconducting devices without access to a cryogenic laboratory. “This field is still developing,” Aziz said. “I want Tennessee to be a place where students don’t simply learn to use future technologies — they help invent them.” Sai Swaminathan: AI devices for community impact Swaminathan is creating a low-cost palm-sized device that puts the problem-solving power of AI into the hands of more community members — quite literally. Tennesseans are increasingly familiar with smart devices like thermostats, speakers, and fitness trackers, which run pre-trained AI models. When one of those models fails, users cannot repair it. When a new situation comes along, they cannot teach the device to handle it. Swaminathan, his students and community partners will use his award of more than $638,000 to develop AI devices that can be trained by users to answer questions that matter locally. The devices will come with a low-powered computer, a sensor such as a camera or microphone, and a simple user interface with a touchscreen, dials or other physical controls. They will work without internet access. Sai Swaminathan “Imagine the benefits AI can have for communities if the technology is designed with communities,” Swaminathan said. “Together we can democratize the power of AI to address what’s most important to community members.” His team has begun working with organizations across Appalachian Tennessee to better understand key regional challenges like food security, water quality and care for older adults. “These organizations have local relationships and understandings, but they’re often small or stretched thin,” Swaminathan said. “Once community members can build and train models by pressing just a few buttons, nonprofits can deploy hundreds of these devices to augment their capacity to achieve greater impacts.” He described two future possibilities. The Knoxville-based organization Socially Equal Energy Efficient Development, which provides pathways out of poverty for young adults, could use the AI devices to train local youth to monitor soil health in its community garden. Volunteers with another organization, Clean Water Expected in East Tennessee, could use the devices to track water pollutants during river cleanups. First, Swaminathan’s team must overcome a major technical hurdle: fitting AI models, which are typically quite large, onto devices with limited memory and processing power. Some will have less memory than a single photo on a phone. His students will then lead workshops with community members to co-design functionality and user interfaces for the devices. “This award is immensely rewarding,” Swaminathan said. “Scientists at the national level are acknowledging the value in our work to ensure computing and AI technologies enable and empower more people and communities.” Explore UT’s AI research — MEDIA CONTACT: Jennifer Johnson (865-974-4448, [email protected])