Four Notre Dame faculty members in the College of Engineering and the College of Science were honored with National Science Foundation (NSF) CAREER Awards — a mark of excellence for early-career researchers who integrate teaching, outreach and scholarship into their work. While each of the honored faculty works on very different problems, they all share a belief in curiosity, persistence and bringing both students and teachers into the journey.
Xiaolong Liu, an assistant professor in the Department of Physics and Astronomy, is pushing the frontier of superconductivity research. He is especially interested in non-reciprocal superconductivity, the idea that current might travel more easily in one direction than the other, even in a superconductor, which usually allows zero-resistance flow. His team is proposing to use a scanning Josephson tunneling microscope, which can probe superconducting current flow at the scale of individual atoms, allowing them to separate intrinsic directional effects from impurities or defects.
“This is an entirely new research direction,” he said. “Detecting directional effects at an atomic resolution has rarely been demonstrated in the past. We have a unique capability to carry out the proposed activities because we have a unique instrument that can do such measurements.”
Liu is also dedicated to education. Through a STEM teachers residency program, he invited middle-school teachers to participate in his lab, co-design curriculum materials and build demonstrations for classrooms or museums.
“We want to get them directly involved in their research so they can have a new perspective on what physicists are doing nowadays,” he said. ”They will codevelop research curriculum materials with us, so they can bring it back to their classrooms.”
To anyone considering a career in physics, Liu’s advice is clear.
“You need to be very self-motivated,” he said. ”You should become exposed to various topics while you can and find something you are passionate about.”
Marc Osherson, an assistant professor in the same department as Liu, works at the intersection of particle physics and data science. He is part of the Compact Muon Solenoid experiment, one of the two giant detectors at CERN’s Large Hadron Collider in Switzerland — the world’s largest particle accelerator. The CMS detector is the size of a building and records the aftermath of proton collisions that happen nearly at the speed of light. From that data, physicists like Osherson search for signs of new particles or phenomena that lie beyond the standard model of physics.
His project, “Probing Low Mass Final States,” focuses on subtle patterns that might reveal undiscovered physics. Osherson revealed how the complexity of his project can seem daunting.
“The technological challenge that we face is dealing with larger and more complex data sets. The main challenge is that we not only have physics questions, but we must also invent the toolkit to see the answers,” Osherson said.
However, Osherson is not discouraged. In fact, he sees the challenge as the fun part of the job.
“It’s something new every day,” he said.
Outreach is also central to Osherson’s CAREER project. Through QuarkNet, he collaborates with high school teachers to introduce cutting-edge particle physics into their classrooms.
“One of the most rewarding moments is when teachers realize that what we work on, even if it seems advanced, is graspable. It’s not magic,” he said.
To undergraduate students interested in physics or data, Osherson offered encouragement.
“You don’t need to be a genius,” he said. ”What matters is that you’re interested in it and are able to dedicate time.”
Nicholas Ramsey, an assistant professor in the Department of Mathematics, studies smoothly approximatable structures, which are infinite objects built from finite approximations. His work explores the limits of classification in mathematics.
“Mathematicians are in the business of classifying objects,” he said. “In some cases, people tried for years to find order and instead found chaos. In the 20th century, it was discovered that you could actually prove classification is impossible in certain situations.”
His focus is on understanding why classification succeeds sometimes and fails others.
“I’ve spent my career trying to live in that gap between tameness and wildness, and to figure out the contours of that geography,” he said.
Ramsey is using his CAREER support to launch a summer school in logic and model theory for advanced graduate students and to expand outreach to mathematicians and students in regions where access to high-level logic is limited. When he learned he would receive this award, he said he felt a mixture of contradictory feelings.
“I was relieved, because there have been major cuts to the NSF funding,” he said. ”I also felt a certain amount of survivor’s guilt, as others were also trying to get NSF funding.”
His biggest challenge in his studies has been grappling with the proof of the classification of finite simple groups, a theorem built piecemeal over decades.
“To move forward, I needed to understand the proof, whether it be the proof as a whole or parts of it,” he said. ”Finding the mental capacity to hold it in my head is going to be an interesting challenge.”
To students thinking about a path in mathematics, Ramsey emphasized community and persistence.
“There are no ‘math’ people,” he said. ”There’s a lot of resistance that people feel as they assume math isn’t something they’re suited for because only a special type of person can do it. I think that’s totally wrong. If there’s a myth about mathematics that needs to die, it’s the one that there are math people who are suited for it.”
Fanxin Kong, an assistant professor in the Department of Computer Science and Engineering, focuses on making learning-enabled cyber-physical systems, like autonomous vehicles, drones and robotic arms, both secure and safe. His NSF CAREER project, “Security Foundations of Safe Learning Enabled Cyber-Physical Systems,” examines new vulnerabilities that arise when machine learning is integrated into real-world systems and develops defenses to ensure their reliable operation. Kong’s group explores approaches such as safe reinforcement learning, neuro-symbolic AI and real-time recovery methods to guard against attacks and failures.
Kong is also dedicated to education outside of Notre Dame. His team introduces students at all levels to robotics and cyber-physical systems through summer programs, annual challenges and undergraduate research opportunities, creating a basis for future innovators in this quickly growing field.
Together, these projects highlight the range of research supported by the NSF CAREER program at Notre Dame.
