Weilun Qiu Defends Dissertation on Modeling Inelastic Material Behavior

Weilun Qiu has successfully defended his doctoral dissertation, “Integrating Statistical Physics and Data-Driven Methods for Modeling Inelastic Material Behavior,” under the supervision of Celia Reina, Associate Professor in Mechanical Engineering and Applied Mechanics (MEAM). His research combines statistical mechanics, machine learning and continuum mechanics to develop computational frameworks for understanding how materials deform and flow beyond their elastic limits.

Bridging Scales in Material Behavior

Materials can exhibit remarkably complex behaviors at the macroscopic scale even when their underlying molecular components are relatively similar. Capturing behaviors such as permanent deformation, phase transformations and flow requires models that account for a material’s microscopic structure and how it changes over time.

Qiu’s dissertation addresses this challenge by developing tools that bridge microscopic physics and continuum-scale material behavior. One part of his research uses machine learning to identify “internal variables,” hidden descriptors that capture a material’s microstructural history, directly from microscopic data. His work connects these data-driven methods with principles from statistical mechanics to ensure that the resulting models remain consistent with thermodynamics. Qiu also developed theoretical and computational methods for studying entropy changes in systems driven away from equilibrium. Together, these contributions offer new approaches for modeling complex, inelastic material behavior.

“My Ph.D. journey has been challenging and ultimately deeply rewarding,” Qiu says. “Research itself was no exception. It took a long time to get my first paper out, and I learned the hard way that meaningful science may not move in a straight line.”

Finding Connection Across Disciplines

Qiu began his Ph.D. at Penn during the COVID-19 pandemic, navigating the uncertainty of starting graduate school in a new country during an already complicated time. Through those challenges, he found himself increasingly drawn to research at the intersection of mechanics, statistical physics and machine learning.

“One of the things that captivates me most is this: at the molecular scale, materials are in many ways similar to one another, and yet at the macroscopic scale they exhibit extraordinarily rich and complex behavior,” he says. “Seeing ideas from such different fields collide is one of the great joys of this kind of research.”

Some of Qiu’s most memorable experiences were not individual breakthroughs, but the conversations that helped produce them. He recalls long discussions with his advisor and lab mates gathered around a whiteboard, working through ideas together.

“There is something irreplaceable about gathering around a whiteboard and working through an idea together, writing, erasing, and slowly watching an outcome take shape,” he says. “Those moments gave me some glimpses into the beauty of science and engineering: asking the right question, finding a possible solution, and collaborating with people who genuinely care about what they are doing.”

Continuing the Research

After graduation, Qiu will join Columbia University as a postdoctoral researcher, where he will continue developing computational frameworks for modeling the mechanics of materials.

For students considering a Ph.D. in MEAM, Qiu encourages them to think carefully about the questions they want to spend years pursuing.

“Invest real time and thought in finding problems that you care about,” he says. “A Ph.D. is a long journey, and the problems you choose will be your constant companions through the highs and the lows. When you are genuinely curious about a question, you’ll find the resilience to push through the inevitable setbacks.”

From Student to Researcher

Qiu extends his gratitude to Reina, whose passion for science provided a constant source of inspiration throughout his Ph.D. He also thanks the faculty and staff in MEAM for their support and his family for their unwavering belief in him, particularly during difficult moments.

Looking back on his time at Penn, Qiu sees the challenges as an essential part of his development.

“This journey has profoundly transformed me,” he says. “I came in as a student, and I leave as a researcher.”