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Selected Methods and Tools for Large Scale Data and Computing

Computational Medicine, on which Sano Centre is focused, poses a lot of interesting challenges which demand research and development from the computing infrastructure perspective. These come from combining the strengths of modeling and simulation based on physics principles with the data-driven approaches of Artificial Intelligence and Machine Learning; from the heterogeneity of computing infrastructures: from HPC to Cloud to the mobile and IoT devices; and from the  distribution and variety of data which requires large-scale analysis.

In this talk, I will briefly introduce examples of projects I have been working on, which tackle some of the above challenges using technologies and methods coming from such domains as scientific workflows, serverless computing and big data analytics. Based on that, I will present current and planned activities of the Extreme Scale Data and Computing Team at Sano.

Maciej Malawski is a Leader of Extreme Scale Data and Computing at Sano Centre and an associate professor at the Institute of Computer Science AGH. Co-author of over 50 international publications including journal and conference papers, and book chapters. Member of technical program committees of premier conferences on scientific, parallel and distributed computing (SC, ICCS, CCGrid, UCC, IPDPS), general co-chair of Euro-Par 2020. His scientific interests include parallel computing, cloud and serverless technologies, distributed systems, resource management and scientific applications, with particular focus on high energy physics (CERN) and biomedical research (Sano Centre).

Maciej Malawski

Sano Centre for Computational Medicine and Institute of Computer Science AGH

Monday, 22 November 2021, 2:00-3:30 PM (CET)

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