Two Tennessee Engineers Win NSF CAREER Awards to Reimagine Superconducting Circuits and Community-Driven AI

Two early-career faculty members at the University of Tennessee, Knoxville, have earned some of the most competitive research honors in the United States, winning National Science Foundation CAREER Awards for projects that push the boundaries of computing in strikingly different directions. Ahmedullah Aziz and Sai Swaminathan, both faculty in the Min H. Kao Department of Electrical Engineering and Computer Science within UT’s Tickle College of Engineering, received the awards through the NSF’s Faculty Early Career Development Program, the foundation’s flagship mechanism for supporting junior researchers who show the potential to become academic role models while advancing research and education at their institutions and across the nation.

Aziz will receive $550,000 over five years to develop the fundamentals of a new generation of superconducting electronics: exceptionally fast, energy-efficient circuits designed to meet the demands of high-performance computing and to serve as controllers for quantum computers that operate in ultra-cold conditions. The award arrives at a moment when the energy appetite of modern computing, particularly the infrastructure behind artificial intelligence, is growing at a pace that conventional semiconductor technology struggles to sustain. Aziz’s project aims to address that challenge at the level of the devices themselves, rethinking how digital information is processed, routed and stored in hardware that bears little resemblance to the silicon chips inside today’s laptops and data centers.

The technical distinction at the heart of Aziz’s work lies in the difference between conventional and superconducting logic. Traditional computing relies on semiconductor transistors that operate at room temperature, switching electrical signals on and off to carry out calculations and make decisions. Superconducting logic systems, by contrast, use superconducting devices that operate at ultra-low temperatures, where electrical resistance effectively vanishes. The result is hardware that is faster and uses very little energy, making it an attractive candidate for the cryogenic environments in which quantum computers must operate. Yet the technology currently lacks important functionalities, a gap that has limited its practical deployment and that Aziz’s project is designed to close.

“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 pursue that goal through a comprehensive methodology: developing predictive device models, designing and evaluating new circuits and larger computing architectures, and fabricating and testing prototypes to validate the underlying concepts. That pipeline, from theoretical modeling to physical hardware, reflects the breadth of expertise required to move superconducting computing from laboratory promise toward engineering reality, and it mirrors the way mature semiconductor technologies were themselves developed over decades of iterative refinement.

The potential payoff is substantial. The resulting technologies could help tackle the rising energy demand of artificial intelligence infrastructure, which now consumes enormous quantities of electricity in data centers around the world. The superconducting logic systems Aziz envisions would also support the development of highly efficient, larger-scale quantum computers by bringing more control, processing and memory functions into the cryogenic environment itself. Today, quantum processors must be tended by control electronics that sit outside the cold zone, creating bottlenecks in wiring, latency and scalability. Embedding more computational capability alongside the quantum hardware could ease one of the field’s most persistent engineering constraints.

Aziz emphasized that the award’s significance extends beyond the laboratory. “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,” he said. In turn, he is providing new opportunities to graduate and undergraduate students at Tennessee. “This funding will support a complete research pipeline. Just as importantly, it will support students who carry out the work,” he said. He also plans to translate certain project elements into hands-on activities for high school students and teachers, allowing them to explore the physics and engineering of superconducting devices without access to a cryogenic laboratory, an outreach effort aimed at broadening participation in a specialized field.

“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.” That ambition situates his project within a larger institutional goal of building research capacity in a region not traditionally associated with advanced computing hardware, and it reflects the CAREER program’s dual mandate of research excellence and educational impact. For a discipline in which the fundamental building blocks are still being defined, involving students early in the invention process carries obvious strategic value for both the field and the state.

Swaminathan’s award, worth more than $638,000, takes a different route toward the same broad goal of making computing more capable and more widely useful. He is creating a low-cost, palm-sized device that puts the problem-solving power of artificial intelligence into the hands of more community members, quite literally. Tennesseans are increasingly familiar with smart devices such as thermostats, speakers and fitness trackers, which run pre-trained AI models. But when one of those models fails, users cannot repair it, and when a new situation arises, they cannot teach the device to handle it. Swaminathan’s project is designed to invert that relationship, giving ordinary users the ability to train the technology themselves.

Swaminathan, his students and community partners will use the award to develop AI devices that can be trained by users to answer questions that matter locally. Each device will combine 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. Critically, the devices will work without internet access, removing a barrier that often excludes rural and under-resourced communities from advanced computing tools. “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 understand key regional challenges such as 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 concrete possibilities: the Knoxville-based organization Socially Equal Energy Efficient Development, which provides pathways out of poverty for young adults, could use the devices to train local youth to monitor soil health in its community garden, while volunteers with Clean Water Expected in East Tennessee could use them to track water pollutants during river cleanups. Before any of that can happen, his students must overcome a major technical hurdle: fitting AI models, which are typically quite large, onto devices with limited memory and processing power, some with less memory than a single photo on a phone. His students will then lead workshops with community members to co-design the devices’ functionality and interfaces. “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.”

Subject of Research: NSF CAREER Awards supporting superconducting logic systems and community-oriented artificial intelligence devices at the University of Tennessee

Article Title: University of Tennessee researchers in electrical engineering and computer science receive NSF CAREER Awards

Article References: University of Tennessee researchers in electrical engineering and computer science receive NSF CAREER Awards. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: NSF CAREER Award, superconducting logic, quantum computing, cryogenic electronics, energy-efficient computing, artificial intelligence, edge AI, community technology, Appalachian Tennessee, University of Tennessee, Tickle College of Engineering, human-centered computing