Advanced Data Analysis & Parallel computing Team – ADAPT

Goals

The acronym “ADAPT” suggests flexibility and evolution, key traits in a fast-moving field like Data Analysis. The group’s objective is to “adapt” cutting-edge computing to solve complex problems, from adapting numerical algorithms to parallel platforms, to adapting machine learning models in HPC environments, or scaling image analyses on GPUs. The notion of “adaptation” also resonates with EU research directions, where data-driven applications tackling emerging economic, social, and environmental challenges require the adaptation and integration of different expertise, such as HPC, applied mathematics, computer science, and statistics.

 Research Activity

ADAPT’s activity focuses on designing models, algorithms, and software tools to discover, understand, and model scientific phenomena from data generated by experiments, tests, and/or simulations of the processes that produce them, opening up to new multidisciplinary challenges in ICT and combining expertise in Computer Science, Applied Mathematics, and Statistics.

The activities combine computational simulation, scientific modeling, analysis, processing, and management of complex, heterogeneous, and large-scale datasets with high-performance computing, parallel computing, and High-Performance Edge Computing techniques. Accurate and efficient techniques and algorithms are developed for data analysis and processing, as well as scientific simulations, also on high-performance architectures. The focus is on load balancing, minimizing data transfers, and reducing time-to-solution.

Application lines include:

• Machine Learning & Artificial Intelligence

• Image Analysis & Processing

• Multilevel models for evaluating the performance of high-performance algorithms

 Application Fields

Application domains include scientific and environmental simulation, medicine, biology, telecommunications, video/image analysis, cultural heritage, and aerospace.

  • AOU Policlinico “Luigi Vanvitelli” (University Hospital), Naples
  • CEINGE – Advanced Biotechnologies
  • CNR (National Research Council) (IBB, IBPM, ICB, IEOS, IGB, IREA, ISASI, ISTC)
  • Esaote S.p.A.
  • Hochschule Wismar
  • IDIS Foundation – City of Science
  • GNCS-INdAM (National Group for Scientific Computing – National Institute of High Mathematics)
  • National Institute of Molecular Genetics (INGM)
  • National Cancer Institute – IRCCS – G. Pascale Foundation
  • National Research University Higher School of Economics (RU)
  • San Martino Polyclinic Hospital – Genoa
  • Sapienza University of Rome
  • Università della Campania Luigi Vanvitelli
  • University of Cagliari
  • University of Cassino and Southern Lazio
  • University of Florence
  • University of Naples “Federico II”
  • University of Naples “L’Orientale”
  • University of Naples Parthenope
  • University of Florida, CAO (USA)
  • University of Sheffield (UK)

Projects

– CNRBiOmics, National Research Center in Bioinformatics for Omics Sciences, https://www.cnr.it/en/node/16209, PIR01_00017.

– “CNRBiOmics, National Research Center in Bioinformatics for Omics Sciences – Strengthening of human capital”, CIR01_00017.

– MATH4CHARM: A mathematical approach to inverse problems arising in cultural heritage preservation and dissemination, https://prin.unica.it/math4charm/

– “Computational toxicology study for the assessment of risk and exposure reduction of heated tobacco products compared to traditional cigarettes,” funded by the ALETHEIA Foundation: The secret to good living.

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