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

Carlos Duarte invited speaker at EU accessibility event

30/11/2023

Carlos Duarte, a LASIGE researcher, was invited to participate in the Concertation event, “Outcomes and Outlooks of Research on Sign Language Technology in Europe”, organized by the research and innovation projects EASIER (Intelligent Automatic Sign Language Translation) and SignON (Sign Language Translation Mobile Application and Open Communications Framework), in collaboration with the LEAD-ME (COST) Action. […]

SATO project’s General Assembly (5th)

28/11/2023

The 5th face-to-face General Assembly (GA) of the SATO project was held by its Siemens Austria partners in Vienna, Austria, from 21 to 23 November 2023. The GA was attended by Pedro Ferreira, the Project Coordinator and Principal Investigator at LASIGE, and Manuel Fonseca, both integrated members of LASIGE, and a researcher from the team, […]

LASIGE researchers featured on 2023 Stanford’s University top 2% most-cited authors

24/11/2023

LASIGE researchers have once again been featured in the top 2% list of the world’s most-cited scientists, which was compiled at Stanford University (USA) and published in Elsevier BV. The database aggregates the top 2 percent scientists of the world from different fields based on standardized citation indications. The data is presented for career-long and […]

RECENT

TALKS

Reading Club in HBI and DSI #10

30/11/2023

Talks @ DI: João Bimbo

23/11/2023

CPS and RDNS meetup: Samaneh Shafee and João Queimado

21/11/2023

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ONGOING

PROJECTS

PlayFam

PlayFam - Plug n' Play: Exploring Asymmetry and Modularity for Inclusive Game Design

Accelerat

Accelerat.ai: Multi-lingual Conversational AI with Modern Contact Centers

RAP

Resource Aware Programming

VAPrevention

Randomised controlled trial and economic evaluation of a person-centred digital intervention to prevent diabetes in high-risk adults

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Projects

PUBLICATIONS

Members

RECENT

PUBLICATIONS

Soraia M. Alarcão, Vânia Mendonça, Cláudia Sevivas, Carolina Maruta, Manuel J. Fonseca. Annotate Smarter, Not Harder: Using Active Learning to Reduce Emotional Annotation Effort. IEEE Transactions on Affective Computing, 1-14, Institute of Electrical and Electronics Engineers (IEEE), 2023 [Biblios]

Bernardo Gomes, José Coelho, Helena Aidos. A survey on traffic flow prediction and classification. Intelligent Systems with Applications, 20, Elsevier BV, 2023 [Biblios]

Duarte Oliveira-Saraiva, João Mendes, João Leote, Filipe André Gonzalez, Nuno Garcia, Hugo Alexandre Ferreira, Nuno Matela. Make It Less Complex: Autoencoder for Speckle Noise Removal—Application to Breast and Lung Ultrasound. Journal of Imaging, 9(10), MDPI AG, 2023 [Biblios]

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SOFTWARE &

TOOLS

Gerador declarações de acessibilidade

A tool for generating accessibility declarations according to the Portuguese model. Team @ LASIGE: Carlos Duarte

OTD (OSINT Threat Detector pilot)

In the scope of the DiSIEM H2020 project, a pilot was built as a service to select cybersecurity threat intelligence from...

OpenRQ

OpenRQ is a Java library that implements the RaptorQ FEC scheme described in RFC 6330. The aim is to provide to...

NAMS

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

KGsim-benchmark

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

DOL

DOL is a Dependent Object-oriented Language featuring dependent types, mutable objects and class-based inheritance with subtyping. The DOL compiler is responsible...

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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.