IMU is a multi-disciplinary unit engaged in research and development activities in Information Technology Management.

Our research is in the following areas:

  • systems that augment human intelligence with advanced data analytics
  • automated machine learning, generative and neuro-symbolic AI approaches with the aim to lower the skill threshold for people and companies to exploit AI benefits
  • mechanisms that support the monitoring and management of computational resources across the cognitive cloud continuum in a secure way
  • blockchain-based transparent information exchange across interoperable data spaces.

Since its establishment IMU contributed actively in sixty (60) research and technology development projects:

  • Forty eight (48) projects were completed during the 1997-2022 period
  • Twelve (12) projects are active during the 2023-2025 period

The total funding of IMU since 1997 exceeds 18,0 million euros.

Research Areas

Research in IMU addresses the whole lifecycle from data analysis to computation to decision.

Our work falls along three strands: Analyse, Compute, Decide.

Analyse: From Data To Insight

We aim to go from data to insight by uncovering hidden patterns, combining information and discovering useful knowledge from the abundance of data available at all levels of human activity (e.g. from mobile apps and wearable devices at the personal level, from industrial sensors at the factory shop floor, from water or transport sensors at the smart city level and online communities at the societal level).

Our research topics in the Analyse phase include:

  • Data and knowledge discovery, sharing and exchange
  • Machine learning and prescriptive data analytics
  • Personalization and recommender Systems
  • Data harmonization and semantic interoperability
  • Linked Open Data and FAIR data management

Compute: From Cloud To Edge

We address research issues that are generated by the availability of computational resources like the issue of context-aware resource allocation across private and public clouds, the exploitation of edge devices for processing computational tasks, the need to provide low latency decisions on live data and the highly secure treatment of information across the computing continuum.

Our research topics in the Compute phase include:

  • Cloud service modeling and management
  • Resource allocation in hybrid environments (cloud, fog, edge)
  • Real-time event-driven service management
  • Security and privacy in cloud environments
  • Context awareness and situation management

Decide: From Intelligence To Prescription

Our research aims to support intelligent decisions by explicitly addressing the uncertainty inherent in the current digital age (e.g. with methods like multiple criteria, fuzzy and linguistic preference modelling), by developing methods of collective intelligence that merge human and automated agents and using advanced decision methods that proactively recommend actions which avoid undesired situations and/or exploit new opportunities.

Our research topics in the Decide phase include:

  • Mathematical programming, simulation and optimization
  • Multiple Criteria Decision Making
  • Probabilistic, fuzzy and linguistic techniques
  • Information aggregation and prediction markets
  • Crowdsourcing and human computation

Application Domains

Of The Future

Specific topics include:

  • Smart manufacturing
  • Supply chain management
  • Predictive maintenance
  • Quality management


Specific topics include:

  • E-participation and e-consultation
  • Citizen-centric services
  • Policy modelling
  • Citizen engagement

Digital Health And Well-Being

Specific topics include:

  • Innovative healthcare
  • Mobile health management
  • Personalised nutrition
  • Secure e-health data exchange


Specific topics include:

  • E-learning and Knowledge Management
  • Idea management
  • Open innovation
  • Social creativity support

And Green Economy

Specific topics include:

  • Smart and green mobility
  • Digital solutions for water management
  • ICT-enabled energy efficiency
  • Behavioral change support