Postdoctoral Appointee at Argonne National Laboratory
Bogota, RAP (Especial) Central, United States
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Summary
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Senior
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Top School
Aurelio Vivas is an adjunct professor and researcher with 11 years of experience specializing in high-performance and data-intensive scientific computing, satellite image processing, and cloud-based workflow deployments. He holds an M.Sc. in Systems and Computing Engineering and is completing a PhD focused on scheduling strategies for efficient data movement in large scientific workflows. Aurelio has combined academic teaching (computer architecture, OS, Python, cloud foundations) with hands-on research and engineering at institutions like Universidad de los Andes and Argonne National Laboratory, contributing to tracing/profiling frameworks for exascale applications and multiple peer-reviewed publications. He has led DevOps and platform deployments for national-scale satellite data cubes and trained teams at IDEAM on operationalizing large-scale geospatial processing. Comfortable moving between low-level HPC concerns and applied machine-learning workflows, he often bridges research prototypes into production-ready platforms. An interesting thread across his career is repeated delivery of scalable, workflow-driven solutions that span CPUs, GPUs, and distributed cloud environments.
11 years of coding experience
7 years of employment as a software developer
Exchange student, Exchange student at Universidad Nacional de Colombia
Ingeniero de Sistemas, Ingeniero de Sistemas at Universidad del Valle
PhD in Engineering Computers Science, PhD in Engineering Computers Science at Universidad de los Andes
Contributions:162 commits, 142 pushes, 5 branches in 5 months
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