NOVA LINCS research is guided by the general theme Science and Engineering for the Global Software-Driven Ecosystem unfolding in two crosscutting, lab-wide, themes:
Principles and Engineering for Global Software SystemsWe develop new principles and engineering for designing, constructing, and supporting informatic systems on emergent computing infrastructures.
User and Communities Empowering ToolsWe provide innovative solutions for empowering users and communities in key technical, societal, and interdisciplinary domains.
The combination of new technology and software are radically changing activities in all areas (e.g., business, industry, culture, media, healthcare, agriculture, inclusion, education, government, entertainment, creativity). This opens new opportunities in industries and businesses, which compete globally for innovative services and products. In Portugal, we clearly perceive a blossom of high-value added players in the IT sector, with high demand for highly qualified staff and prone to seeking to exploit collaborative with academy. This is a maturing movement, in which NOVA LINCS has been an active player.
Advancing the frontier of knowledge and promoting high added-value innovation requires a proper balance of cutting-edge basic and applied research, breadth of expertise in computer science and other fields, and excellent networking between research teams, local and international, and knowledge users. These drivers are actively nurtured within the lab and its groups (Software, Computer, Multimodal, and Knowledge-Based Systems), and supported by our challenge-oriented research program.
Businesses need to innovate quickly to compete in a rapidly changing environment. This calls for rapid, but safe, software evolution and adaptation, ultimately performed by non IT-experts.
We investigate how to support the construction and “live” evolution of trustworthy software systems, focusing on challenges in programming languages, verification and software engineering. Results will be testbeded in domains such as data-centric web apps, cyber physical systems and cybersecurity.
As society increasingly depends on software systems, so increases the expectations of availability, performance and security. This calls for support to build efficient and dependable software.
Data management and data processing are key enablers for building software systems. We research how to create these services for systems that span from the core (e.g. cloud) to the edge (e.g. sensors or mobiles), while providing appropriate levels of security and privacy. Current computing infrastructures and systems are increasingly complex. Managing and efficiently exploring the resources available becomes an important research challenge. We investigate how to deploy computations in resources from data centers to the edge, how to explore parallelism exploring resources available in future hardware architectures and how to build energy-efficient Cyber-Physical Systems.
There is an increasing need for empowering decision makers with improved automated decision and intelligent reasoning systems that use heterogeneous distributed big data sources.
We investigate how to combine knowledge generated using machine learning techniques in different domains with background (human provided) knowledge and how to handle very large-scale combinatorial optimisation problems.
Results are tested in domains such as spatial-temporal forecasting and decision support (e.g., in fire prevention) and logistics problems.
We live in a world where multiple devices are routinely used for interaction and where increasing amounts of multimodal contents, from biometrics and other sensors to the social web, are available. This calls for solutions that help harnessing the potential of this data. We study how to organize and query the information from multiple sources in diverse contexts (e.g. healthcare, cultural heritage, emergency), how to integrate the physical space in solutions for those contexts and how to explore this data in new paradigms of interaction.
As AI becomes pervasive in IT systems for reasoning over data, how to make systems trustable and accountable, respecting the privacy of individual users?
We study techniques for explaining the outputs of AI systems and for providing control on how data from users is being used. We will continue to study how to guarantee that systems incorporate moral behaviour and ethics.
We tackle all these challenges in the context of the research groups focused research themes but also with an eye on the following selected integrative themes:
- Concurrent & Distributed Software
- Computing for Healthcare
- Big Data and Artificial Intelligence
- Computing for Sustainability and Territory
- Computing for Cultural and Arts
- Trustworthy Live Software Development
- Model-driven Engineering for Cyber-Physical Systems