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, and applied computing to life and medical sciences. LASIGE’s activities are organised around six lines of excellence supported by key quality indicators.

Accessibility and Ageing

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 Accessibility and Ageing (AA) 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.

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.

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.

Resilient Distributed and Networked Systems

Resilient Distributed and Networked Systems (RDNS) investigates models, protocols and architectures that are suitable for applications with strong dependability requirements, namely applications that needto 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.

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.

RECENT

NEWS

LASIGE’s work published in the BMC Bioinformatics journal

12/05/2023

The article “DGH-GO: dissecting the genetic heterogeneity of complex diseases using gene ontology”, authored by Muhammad Asif (former LASIGE member) has been published in the BMC Bioinformatics journal, a top-ranked journal (h5-index 75; Scimago Q1). The paper’s co-authors include the LASIGE’s integrated researcher Francisco M. Couto and André Lamurias (also a former LASIGE member). The […]

LASIGE’s PhD Student @ PubhD

10/05/2023

Diana Sousa, LASIGE PhD Student, explained her research in the informal atmosphere of the bar Crew Hassan, held May 9, 2023, participating in the 67th PubhD of Lisbon. Diana investigates machine learning in the clinical and biomedical domain and natural language processing and her talk “Use of machine learning tools in clinical documents to recommend […]

LASIGE publishes at the ICSE 2023

08/05/2023

The paper “The Smelly Eight: An Empirical Study on the Prevalence of Code Smells in Quantum Computing”, co-authored by LASIGE’s research members José Campos and André Souto has been published at the 45th IEEE/ACM International Conference on Software Engineering (core A*). Quantum Computing (QC) is a fast-growing field that has enhanced the emergence of new […]

RECENT

TALKS

19th WideHealth Seminar: Junoš Lukan

19/05/2023

CPS and RDNS meetup: Adriano Mão de Ferro & Rafael Ramires

17/05/2023

LASIGE Workshop on Project Proposal Writing: Lessons Learned from Succesful PIs

17/05/2023

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ONGOING

PROJECTS

SATO

Self Assessment Towards Optimization of Building Energy

DL-CADET

Deep multimodal Learning for breast CAncer DETection

SMART2B

Smartness to existing Buildings

ADMORPH

Adaptive, dynamically morphing, mission and safety-critical CPS

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Projects

PUBLICATIONS

Members

RECENT

PUBLICATIONS

Claudio Reginaldo Alexandre, João Balsa. Incorporating machine learning and a risk-based strategy in an anti-money laundering multiagent system. Expert Systems with Applications, 217, Elsevier BV, 2023 [Biblios]

Diogo F. Soares, Rui Henriques, Marta Gromicho, Mamede de Carvalho, Sara C. Madeira. Triclustering-based classification of longitudinal data for prognostic prediction: targeting relevant clinical endpoints in amyotrophic lateral sclerosis. Scientific Reports, 13(1), Springer Science and Business Media LLC, 2023 [Biblios]

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SOFTWARE &

TOOLS

ARWithMaps+

This work aims to continue the previously developed project, called ARWithMaps, which implements techniques of visualization of points of interest in...

RT-PSS

Real-Time Proactive Secret Sharing Library for RTAI is an implementation of the Shamir’s secret sharing scheme and Herzberg’s proactive secret sharing...

MOOL

Mool is a mini object-oriented language in a Java-like style with support for concurrency, that allows programmers to specify class usage...

T-CBIR

T-CBIR supports searching large scale encrypted image databases based on the images’ visual contents. T-CBIR leverages Searchable Symmetric Encryption (SSE) techniques,...

BFT-SMaRt

BFT-SMaRt is a high-performance Byzantine fault-tolerant state machine replication library developed in Java with simplicity and robustness as primary requirements. Our...

VETA

VETA is a tool that analyses the performance of several variant prediction methods at different levels. Team @ LASIGE: Alcides Fonseca; Pedro...

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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.