Esteban Rangel is an Assistant Computational Scientist in the Computational Science (CPS) Division at Argonne National Laboratory. His research focuses on enabling performance portability and numerical reliability for large-scale scientific applications on emerging exascale systems, with particular emphasis on preparing codes for the Aurora supercomputer and Intel’s Data Center GPU Max Series (PVC). Rangel’s work spans computational performance, software design, and data movement, including the development of cross-architecture programming models, optimization of large-scale I/O using DAOS, and the creation of workflows for analyzing numerical precision and correctness in high-performance simulations.
Rangel has been deeply involved in advancing high-performance computing software ecosystems to ensure scientific applications can effectively exploit next-generation heterogeneous architectures. His recent work integrates compiler toolchains, portable programming models, and scalable storage systems to improve both performance and scientific fidelity on leadership-class systems.
Rangel received his Ph.D. in Computer Science from Northwestern University and subsequently held a postdoctoral appointment at the Argonne Leadership Computing Facility (ALCF), where he worked on large-scale cosmological simulations within the HACC framework.