Norbert Podhorszki
About Norbert Podhorszki
Norbert Podhorszki is a computer scientist at Oak Ridge National Laboratory, specializing in I/O solutions and scientific workflows since 2007. He holds a Master's degree in Computer Science and a PhD in Information Technology, and has previously worked as a research fellow at MTA SZTAKI.
Work at Oak Ridge National Laboratory
Norbert Podhorszki has been employed at Oak Ridge National Laboratory since 2007, where he serves as a Computer Scientist. His role focuses on developing input/output solutions and scientific workflows, particularly for the Oak Ridge Leadership Computing Facility. He enhances end-to-end tools for petascale analysis, which includes components related to I/O, workflow, and dashboards. Podhorszki contributes to the Scientific Computing Group's End-to-End Task, where he applies his expertise in workflow and visualization.
Previous Experience at MTA SZTAKI
Before joining Oak Ridge National Laboratory, Norbert Podhorszki worked as a Research Fellow at MTA SZTAKI from 1995 to 2005. During his ten years at this institution, he engaged in various research projects that contributed to his development as a computer scientist. His experience at MTA SZTAKI laid the groundwork for his later work in scientific computing and workflow development.
Education and Expertise
Norbert Podhorszki holds a Master of Science (MSc) degree in Computer Science from Eötvös Loránd University, which he completed from 1990 to 1995. He further advanced his education by obtaining a Doctor of Philosophy (PhD) in Information Technology from Eötvös Loránd Tudományegyetem. His academic background provides a strong foundation for his specialization in developing I/O solutions and scientific workflows.
Specialization in Scientific Workflows
Norbert Podhorszki specializes in the development of scientific workflows and I/O solutions, particularly for high-performance computing environments. His work at Oak Ridge National Laboratory involves enhancing tools for petascale analysis, which is critical for handling large-scale data efficiently. He plays a key role in improving the functionality and usability of workflow and visualization tools within the scientific computing domain.