LASIGE

LASIGE is a research unit at the Faculty of Sciences of the University of Lisbon, in the field of Computer Science and Engineering. LASIGE gathers experts from several areas of the computing field, including artificial intelligence, machine learning, concurrency, distributed computing, embedded and cyber-physical systems, human-centred computing, information systems, information retrieval, security and privacy, software validation and verification, theory of computing, with an emphasis on computational complexity, and applied computing to life and medical sciences. LASIGE’s activities are organised around seven lines of excellence supported by key quality indicators.

Cyber‐Physical Systems

The LASIGE research line Cyber-Physical Systems (CPS) investigates the functional, human, trustworthiness and timing aspects of cyber-physical systems. This research line focuses on system solutions for offline verification and online monitoring of security- and safety-critical embedded real-time systems, mechanisms for efficient and adaptive interactions among entities in specific scenarios, protocols for autonomous driving scenarios, and visual analytics techniques and tools for exploring heterogeneous datasets from cyber-physical and smart systems, making them more transparent to end-users.

Data and Systems Intelligence

The research line on Data and Systems Intelligence (DSI) strives to devise innovative solutions for large‐scale data problems and complex systems. DSI intersects areas of recent high visibility and impact, such as machine learning and data mining, but also the general fields of artificial intelligence. This highly multidisciplinary research line aims at advancing research and knowledge in the recent flagship application and research domain of data science, web science, and network science.

Dependable and Secure Decentralized Systems

Dependable and Secure Decentralized Systems (DS2) investigates models, protocols and architectures that are suitable for applications with strong dependability requirements, namely applications that need to remain operational despite accidental faults or malicious attacks. The solutions being developed cover a diverse set of objectives, enforcing the prevention, detection and tolerance of failures. The kind of environments that are being contemplated include cloud deployments, highly dynamic and geographically distributed networks, mobile distributed computing, web systems and applications, smart grids and other critical infrastructures.

Health and Biomedical Informatics

LASIGE presents a longstanding record of research contributions in the area of Health & Biomedical Informatics (HBI), by providing innovative solutions for processing biological and medical data, and for supporting the discovery of new biomedical insights. This research line aims to encompass all the scientific work in LASIGE where informatics plays a fundamental role in creating new knowledge in life and health sciences.

Inclusive Human-Computer Interaction

LASIGE presents a longstanding record of research contributions in the area of accessible computing, in assessing, designing, and developing technologies for people with different abilities. The Inclusive Human-Computer Interaction (IHCI) research line gathers all the contributions that seek to evaluate or design interfaces for people with disabilities, older adults, or people suffering from situational impairments.

Reliable Software Systems

Reliable Software Systems (RSS) focuses on modelling techniques and formal analysis approaches to software system structure and behaviour. It aims at enhancing the software engineering practice and particularly the quality of the software.
Its activity ranges from developing theoretical models, languages and techniques to the development of tools that can be used in the real-world software development process, with a clear impact on the workflow of developers and the industry in general. RSS centers its attention on the verification and validation of software, increasing the confidence of developers in their code, especially in complex and error-prone scenarios, such as concurrent and distributed programs.

Theory of Computing

Theory of Computing (ToC) is dedicated to the foundational, theoretical study of computation: What is a computer? What is computation and where does it manifest? What are the capabilities and limitations of different kinds of computers? The method we use to study this question is the mathematical method: we use precise mathematical definitions to model various systems where computation (or a computation-like phenomenon) occurs, and then we use rigorous, deductive reasoning (i.e., mathematical proofs) to understand the behavior and properties of such systems.

RECENT

NEWS

Generating realistic synthetic patients with deep learning to advance healthcare research

26/03/2026

Data scarcity is a major bottleneck for applying deep learning in healthcare, particularly for rare diseases, where small patient populations and privacy constraints limit data availability and sharing. Addressing this challenge, Ruben Branco, LASIGE’s PhD student, published a paper entitled “PatientFlow: Learning to Generate Mixed-Type Longitudinal Clinical Data with Flow Matching” in Artificial Intelligence in […]

Enhancing Trustworthy Robotic Navigation in Uncertain Environments

11/03/2026

LASIGE researcher José Cecílio has successfully obtained funding for the RobustSAR Portugal-Germany Bilateral Cooperation 2024 initiative. The RobustSAR project seeks to build and strengthen a collaborative research network focused on control theory, mobile robotics, networks, and artificial intelligence. The collaboration brings together researchers from the University of Lisboa and TU Bergakademie Freiberg, combining complementary expertise […]

Alcides Fonseca and Leon Ingelse discuss the impact of AI on education

02/03/2026

At the ‘Spring Dialogues’ event, on 25 February 2026, researchers Alcides Fonseca and Leon Ingelse spoke to the Proença-a-Nova school group about the impact that the new generation of generative artificial intelligence is having on education and learning methods. Aiming to demystify what ChatGPT is, how it works and what its limitations are, the speakers […]

RECENT

TALKS

LASIGE TALKS: Alcides Fonseca and Hugo Figueiras

25/03/2026

Workshop @ LASIGE: Inês Neto

18/03/2026

Talks @ LASIGE: Bernardo Malaca

16/03/2026

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ONGOING

PROJECTS

BEiNG-WISE

Behavioral Next Generation in Wireless Networks for Cyber Security

ATTRACT

ATTRACT-EDIH: European Digital Innovation Hub for Artificial Intelligence and High-Performance Computing

I2DT

Intelligent Interoperable Digital Twins

HOFGA

The Hardness of Finding Good Algorithms

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Projects

PUBLICATIONS

Members

RECENT

PUBLICATIONS

Nuno M. Rodrigues, Vanessa F. Fonseca, Renato Mamede, Susanne E. Tanner, Bernardo Duarte, Sara Silva. Integrating elemental and total reflection X-ray spectral fingerprints with machine learning for advanced seafood traceability. Food Control, Elsevier BV, 2026 [Biblios]

Nuno Fachada, João P. Matos-Carvalho, Carlos M. Fernandes. A catch-all discrete distribution: Short description and main properties. Examples and Counterexamples, 8, Elsevier BV, 2025 [Biblios]

Guglielmo Faggioli, Laura Menotti, Stefano Marchesin, Isotta Trescato, Lara Ahmad, Helena Aidos, Anca Loredana Alungulese, Riccardo Bellazzi, Roberto Bergamaschi, Giovanni Birolo, Pietro Bosoni, Maria Fernanda Cabrera-Umpiérrez, Paola Cavalla, Adriano Chió, Arianna Dagliati, Mamede de Carvalho, Piero Fariselli, José Manuel García Dominguez, Sergio González Martínez, Marta Gromicho, Alessandro Guazzo, Aleksandar Jovanović, Borko Kostić, Enrico Longato, Sara C. Madeira, Umberto Manera, José Luis Muñoz Blanco, Eleonora Tavazzi, Erica Tavazzi, Elena Trasobares Iglesias, Vladimir Urošević, Martina Vettoretti, Giorgio Maria Di Nunzio, Gianmaria Silvello, Barbara Di Camillo, Nicola Ferro. The BRAINTEASER Datasets: Clinical, Wearable and Environmental Data for ALS & MS Progression Modeling. Scientific Data, 12, Springer Science and Business Media LLC, 2025 [Biblios]

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SOFTWARE &

TOOLS

KGsim-benchmark

KGsim-benchmark is a collection of 21 benchmark data sets for large biomedical knowledge graphs similarity evaluation. Team @ LASIGE: Catia Pesquita; Rita...

ProPi

ProPi is a tool to statically verify whether message passing programs are free from deadlocks. The tool takes as input a...

Genodedup

GenoDedup is an algorithm that integrates efficient similarity-based deduplication and specialized delta-encoding for genome sequencing data. It increases data reduction gains...

DNA Privacy Detector

The DNA privacy detector is a method that systematically detects privacy-sensitive DNA segments coming directly from an input stream, using as...

NAMS

NAMS (Non-contiguous Atom Matching Structural Similarity) is a free Webtool to calculate similarity between molecules based on the structural/topological relationships of...

DepSpace

DepSpace (Dependable Tuple Space) is fault and intrusion-tolerant secure tuple space implementation. The main objective of the system is to provide...

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About LASIGE

LASIGE is a research and development unit at the Faculty of Sciences of the University of Lisbon, in the field of Computer Science and Engineering.

LASIGE has approximately 250 collaborators, including researchers holding a doctoral degree, PhD and MSc students and other junior researchers, project managers, and a team of system administrators. The current Director is Prof. Alysson Bessani.