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

2nd place in a Federated Learning Competition

20/03/2023

Last week, LASIGE PhD students Susana Nunes, Ricardo Carvalho, Diogo Branco, Diogo Azevedo, and Pedro Cotovio, participated in the Winter School on Trustworthy AI at Hasso Plattner Institute, Potsdam, Germany, where they secured second place in the competition. The event lasted four days, from March 14 to 17, and featured teams from Germany, Macedonia, and Portugal. […]

LASIGE published @ IEEE VR 2023

15/03/2023

The paper “The Design Space of the Auditory Representation of Objects and Their Behaviours in Virtual Reality for Blind People”, co-authored by LASIGE’s João Guerreiro and André Rodrigues (both integrated researchers) and Rodrigo Nogueira (MSc student) has been accepted to IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR 2023), a top-ranked venue […]

Sara Silva interviewed by the SPECIES Society

13/03/2023

Sara Silva was the latest researcher interviewed for the SPECIES Society’s newsletter. The LASIGE’s integrated researcher spoke on how she discovered her now main area of research, Genetic Programming. She talked about her career path, inspirations and choices, and shared her perspective on the future of Machine Learning. Sara Silva is an associate editor of […]

RECENT

TALKS

Talk @ DI/LASIGE: Tom Lenaerts

23/03/2023

LASIGE WORKSHOP 2023

22/03/2023

CPS and RDNS meetup: Hasan Heydari

22/03/2023

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ONGOING

PROJECTS

SATO

Self Assessment Towards Optimization of Building Energy

LAIfeBlood

Artificial Intelligence for Blood Management

DACOMICO

Data Consistency in Microservices Compositions

shiftHRI

Exploring the Transfer of Agency to Older Adults in HRI

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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]

Mendes J., Matela N., Garcia N. . Avoiding Tissue Overlap in 2D Images: Single-Slice DBT Classification Using Convolutional Neural Networks. Tomography, 9(1):398-412, MDPI AG, 2023 [Biblios]

Saeed Osat, Fragkiskos Papadopoulos, Andreia Sofia Teixeira, Filippo Radicchi. Embedding-aided network dismantling. Physical Review Research, 5(1), American Physical Society (APS), 2023 [Biblios]

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SOFTWARE &

TOOLS

VETA

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

DiShIn

DiShIn is a software package provides the basic functions to start using semantic similarity measures directly from a rdf or owl...

Scrapbook

A web platform that supports psychologists in the process of collecting meaningful information about a person, and applying it in reminiscence...

QualWeb online

The QualWeb accessibility evaluation as an online service (source code). Team @ LASIGE: João Vicente; António Estriga; Bruno Andrade; André Santos; Carlos...

KGsim-benchmark

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

ChemRecSys

ChemRecSys (Chemical Compounds Recommender System) is a system for recommending Chemical Compounds, integrating collaborative-filtering algorithms for implicit feedback (Alternating Least Squares...

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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.