Bio
Daniel Rosendo is a Research Scientist in the Workflows and Ecosystem Services group at the National Center for Computational Sciences (NCCS). Daniel's work at Oak Ridge National Laboratory will focus on exploring workflow solutions for integrating advanced data science techniques across the Instrument-to-Edge-to-HPC Continuum at leadership-class scale. His research interests include large-scale workflow management and benchmarking, AI-assisted workflow optimization, provenance tracking, and reproducibility.
Prior to joining ORNL in 2024, Dr. Daniel Rosendo was a research engineer at Inria, France, where he worked on developing open-source software and libraries to support the automated deployment of complex application workflows across large-scale IoT/Edge and Cloud/HPC testbeds.
Daniel received his Ph.D. in Computer Science from the National Institute of Applied Sciences (INSA Rennes and Inria, France). During his Ph.D., Daniel was an intern at Argonne National Laboratory (ANL). His thesis proposes methodologies that aim at overcoming the complexities of understanding, optimizing, and reproducing workflows on the Edge-to-Cloud Continuum. He received an honored mention for the Ph.D. thesis award from BDA (Conference on Data Management) in France.