OPERATIVE UNIT

Institute of Information Science and Technologies “A. Faedo”

CNR-ISTI | Pisa

<span>Institute of Information Science and Technologies “A. Faedo”</span>

The main aim of CNR-ISTI is to advance science and achieve significant results in many Computer Science subdomains, most of them covered by the 13 ISTI’s thematic laboratories. ISTI collaborates with many universities and research institutions at both national and international levels. Collaborations are often related to specific research projects and consortiums.

The Institute also has substantial expertise and reputation in designing and deploying CS infrastructures and in technology transfer activities oriented towards industry or public administration. In addition, ISTI is strongly involved in didactics at the bachelor, master's, and Ph.D. levels. Many ISTI researchers hold courses or seminars in national universities or abroad.

In the Institute there are four laboratories that provide support in different areas:

  • The Knowledge Discovery and Data Mining Laboratory (KDD) has the objective of developing theory, AI techniques, and systems for extracting and delivering useful knowledge out of large masses of data;
  • The InfraScience has the research objective of enabling scientific data infrastructures offering services of Open Science, Data Management, and Data Curation Services;
  • The Artificial Intelligence for Media and Humanities (AIMH) investigates and advances state-of-the-art in the Artificial Intelligence field, specifically addressing applications to digital media and digital humanities, taking into account issues related to scalability;
  • The High Performance Computing Laboratory (HPC) carries out research on algorithms and information systems dealing with computational, data-intensive problems in business, social, and knowledge-based applications.

TNA Offer

The TNA requests can be related to different aspects, such as: 

  • Acquirement of (big) data on food by the employment of available technologies, tools and on a pre-selection of certain food types of interest. Development of algorithms, in accordance with research questions, mainly based on analyzing dietary diversity, food frequency, nutritional importance of different food groups, and models for determining food consumption behaviors. 
  • Public debates study, using state-of-the-art algorithms for supervised prevalence estimation to track collective sentiment. Analysis of discussion using data from online social networks in order to investigate topics that are relevant for society, as well as phenomena such as opinion polarization and echo chambers. 
  • Development of innovative methodologies to help decision-makers in producing policies and strategies for mobility, urban sustainability and improve environmental performance concerning digitalization, energy, water, waste management, CO2 emissions, and pollution.
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