KU doctoral student selected for prestigious training program in extreme-scale computing

University of Kansas doctoral student Christina Hymer was selected to participate in the 2026 Argonne Training Program on Extreme-Scale Computing (ATPESC), a highly competitive program that prepares the next generation of computational scientists to harness the world’s most powerful supercomputers for scientific discovery.

Hosted by the U.S. Department of Energy’s Argonne National Laboratory, ATPESC took place July 26 through Aug. 7, 2026. The intensive two-week program brought together 75 graduate students, postdoctoral researchers and computational scientists from around the world for advanced instruction in high-performance computing (HPC), artificial intelligence and computational science. Participants were selected through a competitive application process based on their technical expertise, research accomplishments and potential to advance scientific discovery through leadership-class computing systems.

During ATPESC, the group primarily used the supercomputer Aurora, housed at the Argonne Leadership Computing Facility. According to Hymer, Aurora is an exascale computer, capable of performing at least one quintillion floating-point operations per second. The United States owns and operates three of the five fastest supercomputers in the world. At ATPESC, researchers had access to two of them, Aurora and Frontier, along with others that aren’t in the top five.

“The training program gave me a much broader perspective on what it means to do research in HPC,” Hymer said. “I went into the program with experience developing mathematical algorithms and implementing them with parallel computing, but ATPESC challenged me to think about the entire computing system and how all its pieces interact to affect outcome and performance. I was constantly finding connections between what we were learning and problems in my own research, and I came home with a lot of new ideas that I’m excited to explore and some that I'm already implementing.”

Hymer is pursuing her doctoral degree in mechanical engineering at KU, where her research focuses on bioengineering applications, high-fidelity simulations and parallel programming and optimization. She conducts her research under the advisement of Suzanne Shontz, professor in the Department of Electrical Engineering and Computer Science (EECS) and director of the Institute for Information Sciences’ (I2S) Mathematical Methods and Interdisciplinary Computing Center (MMICC).

Throughout ATPESC, Hymer received hands-on instruction from internationally recognized experts in high-performance computing, artificial intelligence and computational science. The curriculum included advanced computer architectures, programming models for modern supercomputers, numerical algorithms, performance optimization, machine learning, data science and software sustainability. Participants also gained practical experience developing applications for current and emerging exascale computing systems.

The program aligns closely with Hymer’s research interests. Techniques for parallel computing and scalable software development are essential for accelerating mesh generation and enabling complex bioengineering simulations to run efficiently on today’s most advanced supercomputers.

Hymer’s selection reflects both her promise as a computational researcher and KU’s growing leadership in computational science and high-performance computing. Through faculty mentorship and interdisciplinary research centers such as I2S and MMICC, KU continues to prepare graduate students to address scientific and engineering challenges that require advanced computational methods.

Since its inception in 2013, ATPESC has become one of the nation’s premier training programs for researchers whose work depends on high-performance computing. Alumni have gone on to lead research efforts at universities, national laboratories and industry, applying advanced computational techniques to challenges ranging from engineering and materials science to biology, climate modeling and artificial intelligence.