Data Science and Artificial Intelligence

Collecting, managing, analysing, interpreting and visualising large and complex datasets. Data mining. Applications of Artificial Intelligence to Astrophysics.

The Data Science and Artificial Intelligence program at our institute deals with the collection, management, analysis, interpretation, and visualization of large and complex datasets, and with the development of new AI algorithms and techniques, making them a vital aspect of research in astrophysics. Our research in data science was carried out through the MeDIA program (Methods and Methodologies for Data and Image Analysis), which focuses on data science aspects related to astrophysical data analysis, space missions, and experiments that the institute is involved in.

Recently, we have launched a new project called MADELEinE, which is partly conducted within the framework of the National Centre for HPC, Big Data, and Quantum Computing – Spoke 2 – Fundamental Research and Space Economy. MADELEinE (an acronym for Machine and Deep Learning in Experiments) aims to investigate the feasibility and efficiency of Artificial Intelligence approaches in various case studies of astrophysics.

Our group is focused on the development and application of advanced data analysis and machine learning techniques to solve problems in different scientific fields. We are particularly interested in creating new methods for data-driven analysis, with a strong emphasis on applications in high energy astrophysics, to improve our understanding of high energy phenomena in the universe.

Our research covers a wide range of topics within the field of Data Science and Artificial Intelligence, including:

  • Machine learning and deep learning: We work on developing new algorithms and techniques for supervised, unsupervised, and semi-supervised learning, as well as deep learning methods for large-scale and complex data. We also explore various areas of application such as computer vision, natural language processing, and prediction of time series.
  • Computer vision. We work on developing new methods for image and video analysis, including object detection, image segmentation, and image captioning.
  • Data mining. We study methods for extracting useful information and knowledge from large and complex data sets, including techniques for clustering, classification, and association rule mining.
  • Predictive modeling. We work on developing new methods for prediction and forecasting, including time series analysis, survival analysis, and causal inference.

Our group comprises of a multidisciplinary team of researchers with expertise in astrophysics, computer science, statistics, and mathematics. We collaborate with other researchers and institutions in the field to achieve our research goals and make new discoveries. We also participate in outreach activities to share our research with the public and inspire the next generation of scientists.

We regularly present our findings at conferences and publish our research in scientific journals. We also offer opportunities for students and researchers to join our team and contribute to our ongoing projects.

If you are interested in learning more about our research or would like to collaborate with us, please do not hesitate to contact us. We are always looking for new opportunities to work with other researchers and institutions in the field.

Read more:  HPC, Big Data and Quantum Computing; MADELEinEMeDIAJEM-EUSO.