Research Topics

The research topics described in the table below are investigated by faculty and researchers of the three University partners (i.e. Pisa, Florence and Sienna) and of CNR Pisa (i.e. ISTI and IIT). All of these investigations are supported by national and international projects at academic or industrial level.

Algorithm Design

Design, analysis, and experimentation of efficient algorithms and data structures with applications to the analysis and combinatorics of biological sequences, information retrieval, data compression, indexing and searching over big data. Research also covers graphs and network analytics, mobile agents and robots, logic synthesis of Boolean functions and circuits, and image analysis.

Cognitive Software Engineering

Cognitive aspects in software engineering, with a focus on requirements elicitation, verification, and formal modeling. Research activities include work on smart city infrastructure and corresponding software architectures for data collection and analysis. Application-centered testing ground for emerging Machine Learning techniques have been exploited.

Computational Systems Biology

Develop and apply advanced computing methods and technologies for the applicative domains of systems medicine, systems pharmacology and systems nutrition. Skills cover multi-omics data analysis and integration, biomarker identification, network biology and pathway analysis, modeling and simulation. The research activities are related to the design of novel formal methods and ad hoc language development, visualization techniques, stochastic and hybrid simulation algorithms.

Computer Networks

Research focuses on the development of algorithms for packet scheduling in input queued switches for internet routers and on protocols for RFID systems management.

Cyber Security

Research focuses on different aspects of security. On the one hand, it develops models and software construction methods for secure systems based on programming language technologies. Rigorous reasoning and formal methods for security are investigated at foundational level. Application security is studied by specifying, enforcing, verifying, and testing security and privacy policies.

Data Science and Big Data

Research tackles several applications and challenges associated to big data management and analytics with results, among the other, in data compression, search and mining, as well as in analytics and data visualization. Applications have been built related to well-being and sport analytics, complex network analysis and green computing. Special attention has been placed on the interplay between data science and human rights, privacy and digital ethics.

Distributed and High-Performance Computing

Research focuses on different aspects of parallel programming models and tools, including structured parallel programming frameworks exploiting high performance data stream processing, autonomic computing and energy aware parallel computing. The research activities contribute to the development of FastFlow, a structured parallel programming framework providing efficient and nestable parallel pattern objects.

Distributed Ledgers for Social Good

Development of Distributed Ledger Technology infrastructures (DLT), aka blockchains, to support a variety of applications ranging from healthcare, digital identities, e-voting, and IoT systems. The main goal is to study and propose DLT-infrastructures that allow the largest number of people to benefit from trustworthy, completely distributed services.

Formal Methods

Methodologies for the specification and analysis, both qualitative and quantitative, of systems featuring aspects of concurrency and distribution. The overall approach is characterized by the application of (co-)algebraic and logical methods as well as static analysis techniques to well-known models of concurrency, including Petri nets, event structures, string diagrams and graph transformation systems.

HCI and Software for Disable People

Research falls within the field of human computer interaction and didactic software with special attention to people with disabilities: visually impaired, Autism Spectrum Disorder People and cognitive disabilities. More specifically the main areas of interest are: human centered computing, participatory design, software for disabled people.

Intelligent Cyber-physical Systems

Two independent research lines (Internet of Things and Machine Learning) collaborate towards the design of the internet of intelligent things integrating distributed sensing, smart signal processing, ambient intelligence via Machine Learning.

Machine Learning and Artificial Inteligence

Development of Machine Learning methodologies for learning in structured domains (sequences, trees, graphs), on the analysis of their computational properties, on the application to innovative Artificial Intelligence and interdisciplinary fields. The design of new learning methods includes Neural Networks, Probabilistic, Reservoir Computing, Deep Learning, and Kernel-based approaches.

Mathematical Optimization

Several methodologies related with algorithmic solutions for mathematical optimization are considered. This includes network optimization, combinatorial optimization and polyhedral analysis, non-linear optimization (possibly with integer restrictions), vector optimization, variational problems, and game theory. Besides foundational research, applications of the proposed methods have been realized in a wide array of real-world problems in areas such as transportation, logistics, health-care, energy, telecommunication and others, often time in collaboration with industries.

Natural Language Technologies

Development of the Universal Dependency treebank for Italian, and design and implementation of NLP tools applied to parsing, opinion mining, named entity recognition and linking and question answering. Successful applications are in healthcare and in the analysis of social media.

Service-oriented, Cloud and Fog Computing

Methodologies and open-source prototypes for automating management and portability of cloud applications and supporting multi-objective (QoS, resources, cost) predictive deployment of Fog/Edge applications. It also develops DevOps software engineering models and techniques, in particular container orchestration and micro-services architectures.