The world is a complex system, and understanding it scientifically requires advanced computational resources and approaches. Engineers design the most powerful computers on Earth in order to model and simulate physical systems such as global climate, the expansion of the universe, and the behavior of matter at an atomic level. But today, high performance scientific computing means more than just supercomputers running numerical models, expanding to large-scale data analysis, AI and machine learning, visualization, and distributed and heterogeneous hardware systems.

UChicago CS researchers are changing the face of high performance computing (HPC), creating new computing paradigms at scale for understanding physical, biological, social, and ecological systems and answering the most significant questions facing society. Faculty lead efforts to apply the latest AI and data science approaches for scientific discovery, from computational imaging and spectroscopy to bioinformatics, neuroscience, and agriculture. In these areas, as well as in the development and application of new exascale systems such as Aurora, UChicago CS benefits from a strong partnership with Argonne National Laboratory.