Summary
Andres Sewell is a PhD candidate in Computer Science specializing in high-performance computing and scientific visualization, with eight years of software experience and hands-on work on leadership-class supercomputers. He has driven scalable in situ workflows and distributed 3D Gaussian splatting systems in collaboration with Argonne and Lawrence Livermore National Laboratories, contributing code and publications to the Ascent in situ visualization framework. Andres combines low-level performance optimization with practical system design—evidenced by refactoring Radiography (Rover) for massive MPI-scale rendering and creating hybrid scheduling to avoid GPU contention. He’s equally comfortable prototyping ML-driven reconstruction pipelines and building production-ready analysis interfaces that enable human-in-the-loop steering of running simulations. Based in Ogden, Utah, he’s passionate about squeezing performance from both HPC clusters and personal gaming rigs, a hobby that seeded his long-term interest in systems and graphics. Andres is seeking full-time roles starting Fall 2026 that tackle challenging problems in HPC, visualization, or distributed optimization.
8 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Utah State University
Associate of Science - AS, Computer Science, Associate of Science - AS, Computer Science at College of Southern Idaho
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Idaho State University
Spanish, American Sign Language