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

SMART2B’s project kick-off

21/09/2021

The EU H2020 SMART2B’ project (coordinated by EDP NEW) virtual kick-off meeting started today, September 21st, 2021 and was attended by Pedro Ferreira, LASIGE integrated member and Ciências ULisboa Professor, who leads LASIGE participation in the consortium, and Guilherme Carrilho da Graça, also a Ciências ULisboa Professor and a researcher at Instituto Dom Luiz (IDL). […]

Best Paper Award @ SRDS’21

20/09/2021

Alysson Bessani, LASIGE’s integrated member, won the best paper award at the 40th International Symposium on Reliable Distributed Systems (SRDS 2021), co-authored with Hans P. Reiser and Christian Berger. The paper “Making Reads in BFT State Machine Replication Fast, Linearizable, and Live” identified a 20-year-old dormant bug on MIT’s Practical Byzantine Fault Tolerance (PBFT) – […]

Best Student Paper Award @ INForum 2021

15/09/2021

Catarina Gamboa, at the time LASIGE’s MSc student, won the award for best student poster at INFORUM2021 for the work entitled “LiquidJava: Adding Lightweight Verication to Java”, co-authored with Paulo Alexandre Canelas dos Santos, Christopher S. Timperley, and Alcides Fonseca. Another LASIGE distinction was the article “Deteção Automática de Conflitos Semânticos” by Nuno Castanho, LASIGE’s […]

RECENT

TALKS

RSS Meetup September#1: Pedro Rocha

22/09/2021

5th WideHealth Seminar: Hristijan Gjoreski

14/09/2021

RSS Meetup July#3: Catarina Gamboa

22/07/2021

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ONGOING

PROJECTS

AWESOME

Awareness While Experiencing and Surfing On Movies through Emotions

LAIfeBlood

Artificial Intelligence for Blood Management

LEMON

LEtter learning through MOtor training: Neurocognitive specialization for the written code investigated with electrophysiological, eye-tracking, and computational tools

DKG

Distributed Knowledge Graphs

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Projects

PUBLICATIONS

Members

RECENT

PUBLICATIONS

Marcel Müller, Marta Gromicho, Mamede de Carvalho, Sara C. Madeira. Explainable Models of Disease Progression in ALS: Learning from Longitudinal Clinical Data with Recurrent Neural Networks and Deep Model Explanation. Computer Methods and Programs in Biomedicine Update, Elsevier BV, 2021 [Biblios]

Naercio Magaia, George Mastorakis, Constandinos Mavromoustakis, Evangelos Pallis, Evangelos K. Markakis. Intelligent Technologies for Internet of Vehicles, Springer International Publishing, Internet of Things, 2021 [Biblios]

Filipe Galvão, Soraia M. Alarcão, Manuel J. Fonseca. Predicting Exact Valence and Arousal Values from EEG. Sensors, 21(10), MDPI AG, 2021 [Biblios]

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SOFTWARE &

TOOLS

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...

BFT ordering service for Hyperledger Fabric

This is a Byzantine fault-tolerant (BFT) ordering service for Hyperledger Fabric. This BFT ordering service is a wrapper around BFT-SMaRt, a...

MIL

MIL (Multithreaded Intermediate Language) is an assembly language targeted at an abstract multi-processor equipped with a shared main memory. Each processor...

SCFS

SCFS is a cloud-backed file system that provides strong consistency even on top of eventually-consistent cloud storage services. Its build on...

CIDS

CIDS (Citation Impact Discerning Self-citations) is a user-friendly web tool that calculates different citation statistics, such as the h-index and g-index.

NAMS

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

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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. Vasco T. Vasconcelos.