Five University of Michigan Researchers Elected APS Fellows

Five University of Michigan faculty members have been elected fellows of the American Physical Society, an honor that recognizes achievement in physics and service to the physics community. Fewer than 0.5% of APS members are selected each year, making the fellowship a selective distinction rather than a routine marker of seniority. The new fellows work across plasma theory, quantum materials, propulsion and computational methods. Their fields look disparate, but each depends on tools for understanding how complex physical systems behave—and on researchers who can connect theory, computation and experiment.

Advances in theory and computation

Scott Baalrud, a professor of nuclear engineering and radiological sciences, was cited for advances in plasma kinetic theory, including research on warm dense matter, strongly magnetized plasmas and low-temperature plasmas. These areas involve different physical conditions, but all require researchers to account for the collective behavior of charged particles. His theoretical work also addresses plasma-boundary interactions, where conditions at the edge of a plasma can shape how it behaves and interacts with surrounding materials. The applications listed for this research range from fusion energy and high-energy-density physics to electric propulsion and microelectronics. That breadth reflects how a shared set of physical questions can matter across fields with very different practical aims.

Emanuel Gull, professor of physics, was recognized for numerical methods used to study strongly correlated electron systems. In these systems, interactions among electrons can make their behavior difficult to describe by treating each particle independently. Gull’s contributions include quantum impurity solvers for systems in equilibrium and out of equilibrium, as well as applications to correlated materials. Such methods give researchers ways to model conditions that can be challenging to capture through experiment alone, while still helping connect calculations to material behavior. His recent work also touches on quantum computing and machine-learning methods for quantum field theories—areas where computational tools are expanding the questions researchers can investigate.

Dominika Zgid, professor of chemistry and physics, was honored for foundational work on ab initio many-body methods for molecules and solids, including self-energy embedding theory and self-consistent perturbation theories. These approaches help researchers account for interactions within systems whose properties can’t be understood by looking at individual components in isolation. Her group develops theoretical tools to study properties that experimentalists can measure, including electron behavior in molecules and systems relevant to quantum computing and molecular magnets. That link between calculation and measurable outcomes matters: models are most useful when they can be tested against observable behavior. Here’s the thing: computational physics doesn’t replace experiments; it can help researchers decide what to measure and how to interpret what they find.

Physics leadership and high-speed propulsion

Cagliyan Kurdak, a physics professor, was recognized for sustained efforts to broaden participation in graduate physics education and expand interdisciplinary career paths. That citation points to work on the academic structures around physics as well as research within it: who gets access to graduate training, and what kinds of work those students can pursue. His experimental research examines low-temperature and nanoscale condensed matter, including low-dimensional electron systems and conduction in topological insulators. A Michigan faculty member since 1998, Kurdak directed the Applied Physics Program from 2010 to 2025. His fellowship therefore recognizes contributions that span experimental physics, education and program leadership. And this is the part most people overlook: scientific institutions shape which questions get asked by shaping who can take part.

Venkat Raman, professor of aerospace engineering and the James Arthur Nicholls Collegiate Professor of Engineering, was cited for work on computational methods and fundamental insights in rotating detonation engines and high-speed propulsion. These engines involve complex interactions between combustion and moving gases, making both physical understanding and computational analysis relevant to their study. Raman leads the Advanced Propulsion Concepts Lab and directs the Center for Prediction, Reasoning and Intelligence for Multiphysics Exploration (C-PRIME). The center brings artificial intelligence and computational and computer science methods to applications across fields of national interest. Its remit reflects a broader trend in research: using computation to study systems where multiple physical processes interact. The promise is greater analytical reach; the test is whether the methods produce insights that researchers can validate and apply.

What the selections say about the field

The five selections reflect the breadth of Michigan’s contributions to physics, from foundational models of matter to engines designed for flight beyond the speed of sound. They also show how much modern physics depends on work that crosses disciplinary boundaries. Plasma theory connects to engineering applications; methods developed to describe electrons can inform research on materials and quantum computing; and propulsion research draws on computation alongside experiments and physical models.

The fellowship is a form of peer recognition, but the range of citations gives it a wider significance: it captures several ways researchers contribute to the field, from developing theory and numerical tools to building programs and widening access to education. The distinctions don’t, by themselves, establish how quickly any application will advance. That said, they identify bodies of work that other physicists have judged consequential to their disciplines and communities.

If you're working in this space, the shared thread is hard to miss: progress often depends on better ways to represent systems that are too complex for simple models. The numbers here are selective, but the subject matter is expansive. Still, recognition is a snapshot of achievement, not a forecast. The harder work—testing models, building on results and training the next generation—continues after the fellowship announcement.