Main Projects

  • is the H2020 European Research Infrastructure for Big Data and Social Mining which involves more than 100 data scientists affiliated to Universities and Research Centres of 7 european countries. UniPI and CNR are leading partner of this RI.
  • Spark is a Stanford-UniPI research collaboration whose goal is advancing academic discoveries and innovative solutions by addressing health challenges through novel computational methods and tools in the field of systems medicine and pharmacology for the benefit of patients and helps the translation of these results through education and project management best practices.
  • MIT-UniPI is a research collaboration between the Massachusetts Institute of Technology and the University of Pisa whose goal is advancing academic discoveries and innovative solutions in all scientific areas.
  • RePhrase is a H2020 project that focuses on producing new software engineering tools, techniques and methodologies for developing data-intensive applications in C++, targeting heterogeneous multicore/manycore systems that combine CPUs and GPUs into a coherent parallel platform.
  • Planares is an H2020 project that develops innovative optimization tools to support the main stakeholders of the European energy system (TSOs, DSOs, Utilities, Energy providers…) by helping them taking better decisions regarding the development and operation of their energy portfolio, also considering the emerging technologies and innovative flexibility sources while maintaining a high level of reliability.
  • LIST-IT is a MIUR-SIR grant that deals with machine learning and deep learning models for non-isomorph transductions, that is a generalization of supervised learning to the structured domain, where both the input sample and the output prediction are trees of unconstrained topology. Applications are in natural language processing (text summarization and machine translation as parse tree transduction) and bioinformatics (modeling cancer cell evolution as clonal tree transduction over time).
  • Data Compression and Sequence Analysis is a MIUR-SIR grant that exploits methods from Combinatorics on Words, developing algorithms and data structures for the treatment of strings, mainly datasets from Next-Generation Sequencing (NGS) technologies or third generation sequencing technologies.
  • the PhD program also hosts three Marie Curie Innovative Training Networks (ITNs): “MINOA: Mixed-Integer Nonlinear Optimization Applications”, “NeCS: European Training Network for Cyber Security” and “EVOCATION: Advanced Visual and Geometric Computing for 3D Capture, Display, and Fabrication”.
  • Students of the PhD program are also involved in industrial grants financed by Google, Bloomberg, ARM, Huawei, etc. etc. as well as they can spend internship periods of R&D at one of the about 50 companies that have applied to our “PhD internship program” launched in 2018.