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Facts & Numbers
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Presentation

Artificial Intelligence and Decision Support

At LIAAD, we work on the very strategic area of Data Science, which has an increasing interest worldwide and is critical to all areas of human activity. The huge amounts of collected data (Big Data) and the ubiquity of devices with sensors and/or processing power offer opportunities and challenges to scientists and engineers. Moreover, the demand for complex models for objective decision support is spreading in business, health, science, e-government and e-learning, which encourages us to invest in different approaches to modelling.

Our overall strategy is to take advantage of the data flood and diversification, and to invest in research lines that will help reduce the gap between collected and useful data, while offering diverse modelling solutions.

At LIAAD, our fundamental scientific principals are machine learning, statistics, optimisation and mathematics.

Latest News
Computer Science

INESC TEC researcher collaborated with the winner of the Abel Prize in Mathematics

The Norwegian Academy of Science and Letters awarded Dennis Sullivan the Abel Prize in Mathematics, the highest award in the field, comparable to the Nobel Prize. The north American mathematician is one of the world's leading experts in the development of the Theory of Renormalization in Dynamic Systems. INESC TEC researcher Alberto Adrego Pinto had the opportunity to collaborate with Dennis Sullivan in the 1990s. This collaboration led to scientific work with great impact on the researcher’s career. 

06th April 2022

Computer Science

Technology that reduces treatment time for cancer patients wins digital innovation award

The Gentil – Text Mining project won the Portugal Digital Awards in the Best Future of Work Project category, which acknowledges the best initiative related to employees' productivity and effectiveness.

06th January 2022

Computer Science

INESC TEC part of a project to develop a Smart Process Management System

INESC TEC, through the Centre for Information Systems and Computer Graphics (CSIG) and the Artificial Intelligence and Decision Support Laboratory (LIAAD), participates in the SIGIPro project, in partnership with the Faculty of Sciences of the University of Porto and the company Expandindustria, SA.

01st July 2021

Computer Science

INESC TEC researchers acknowledged for scientific excellence in machine learning and data mining

The European programme IACOBUS granted the "Scientific Publications (Papers)" award to a team of researchers from INESC TEC’s Artificial Intelligence and Decision Support Laboratory (LIAAD), led by João Gama.

23rd June 2021

Computer Science

INESC TEC participates in an initiative for global digital inclusion

INESC TEC, through the Laboratory of Artificial Intelligence and Decision Support (LIAAD), contributes to a project focusing on identifying and classifying people’s opinions and feelings about products and services, included in texts written in different Nigerian languages.  

18th June 2021

Interest Topics
075

Featured Projects

FORM_I40

Formação Indústria 4.0

2022-2022

DAnon

Supervised Deanonymization of Dark Web Traffic for Cybercrime Investigation

2022-2023

AgWearCare

Wearables para Monitorização das Condições de Trabalho no Agroflorestal

2021-2023

SADCoPQ

Sistema de Apoio à Decisão no Controlo Preditivo da Qualidade na Indústria Metalomecânica da Precisão

2021-2023

DigitalBudget_VE

Aplicação computacional para orçamentação automática de postos de carregamento de VE

2021-2021

XPM

eXplainable Predictive Maintenance

2021-2023

SSPM

Student Success Prediction Model

2021-2022

OnlineAIOps

Online Artificial Intelligence for IT Operations

2021-2023

SIGIPRO

Sistema inteligente de gestão de processos habilitados espacialmente

2021-2023

AI_Sov

AI Sovereignty

2021-2021

CloudAnalytics4Dams

Gestão de Grandes Quantidades de Dados em Barragens da EDP Produção

2021-2021

City Analyser

An agnostic platform to analyse massive mobility patterns

2020-2022

PORT XXI

Space Enabled Sustainable Port Services

2020-2022

Training4DS

Formação Avançada em Data Science - Altice Labs

2020-2020

PFAI4.0

Programa de Formação Avançada Industria 4.0

2020-2021

HumanE-AI-Net

HumanE AI Network

2020-2023

MetaFLow

A Meta Learning work-flow for a Low Code Platform

2020-2021

PAIQAFSR

Provision of advisory inputs and quality assurance of the final study report.

2020-2020

TRF4p0

Digital revolution of power transformers

2020-2023

Continental FoF

Fábrica do Futuro da Continental Advanced Antenna

2020-2023

AIDA

Adaptive, Intelligent and Distributed Assurance Platform

2020-2022

PAFML

Investigação e desenvolvimento para aplicação de Machine Learning a dados de pacientes com Paramiloidose

2020-2023

SLSNA

Prestação de Serviços no ambito do projeto SKORR

2020-2021

MINE4HEALTH

Text mining e clinical decision-making

2020-2021

Text2Story

Extracting journalistic narratives from text and representing them in a narrative modeling language

2019-2022

T4CDTKC

Training 4 Cotec, Digital Transformation Knowledge Challenge - Elaboração de Programa de Formação “CONHECER E COMPREENDER O DESAFIO DAS TECNOLOGIAS DE TRANSFORMAÇÃO DIGITAL”

2019-2021

PROMESSA

PROject ManagEment intellingent aSSistAnt

2019-2022

RISKSENS

Market Risk Sensitivities

2019-2020

NDTECH

NDtech 4.0 - Smart and Connected - Estudo e Caderno de Encargos

2019-2019

RAMnet

Risk Assessment for Microfinance

2019-2021

HOUSEVALUE

Estimativa de Valor de Avaliação de Imóveis

2019-2019

Humane_AI

Toward AI Systems That Augment and Empower Humans by Understanding Us, our Society and the World Around Us

2019-2020

MLABA

Machine Learn Based Adaptive Business Assurance

2019-2019

Moveo

Prestação de serviços de investigação e desenvolvimento relativos ao sistema MOVEO

2019-2019

FIN-TECH

A FINancial supervision and TECHnology compliance training programme

2019-2021

FailStopper

Early failure detection of public transport vehicles in operational context

2018-2021

TerraAlva

Terr@Alva

2018-2019

MaLPIS

Aprendizagem Automática para Deteção de Ataques e Identificação de Perfis Segurança na Internet

2018-2022

MDG

Modelling, dynamics and games

2018-2022

NITROLIMIT

Life at the edge: define the boundaries of the nitrogen cycle in the extreme Antarctic environments

2018-2022

RUTE

Randtech Update and Test Environment

2018-2020

SKORR

Advancing the Frontier of Social Media Management Tools

2018-2021

FAST-manufacturing

Flexible And sustainable manufacturing

2018-2022

FLOWTEE

Desenvolvimento de um programa que monitorize automaticamente os níveis de bem-estar (ou felicidade) dos funcionários, a partir de dados disponíveis online

2018-2019

MDIGIREC

Context Recommendation in Digital Marketing

2017-2018

NEXT-NET

Next generation Technologies for networked Europe

2017-2019

RECAP

Research on European Children and Adults born Preterm

2017-2021

SmartFarming

Ferramenta avançada para operacionalização da agricultura de precisão

2016-2018

PANACea

Perfis para Anomalias Consumo

2016-2019

BI4UP2

Business Intelligence (BI) Tool

2016-2017

Dynamics2

Dynamics, optimization and modelling

2016-2019

CORAL-TOOLS

CORAL – Sustainable Ocean Exploitation: Tools and Sensors

2016-2018

MarineEye

MarinEye - A prototype for multitrophic oceanic monitoring

2015-2017

FOUREYES

TEC4Growth - RL FourEyes - Intelligence, Interaction, Immersion and Innovation for media industries

2015-2019

NanoStima-RL5

NanoSTIMA - Advanced Methodologies for Computer-Aided Detection and Diagnosis

2015-2019

iMAN

iMAN - Intelligence for advanced Manufacturing systems

2015-2019

NanoStima-RL3

NanoSTIMA - Health data infrastructure

2015-2019

NanoStima-RL4

NanoSTIMA - Health Data Analysis & Decision

2015-2019

SMILES

SMILES - Smart, Mobile, Intelligent and Large scale Sensing and analytics

2015-2019

FOTOCATGRAF

Graphene-based semiconductor photocatalysis for a safe and sustainable water supply: an advanced technology for emerging pollutants removal

2015-2018

SEA

SEA-Sistema de ensino autoadaptativo

2015-2015

MAESTRA

Learning from Massive, Incompletely annotated, and Structured Data

2014-2017

BI4UP

Business Intelligence (BI) Tool

2014-2014

SIBILA

Towards Smart Interacting Blocks that Improve Learned Advice

2013-2015

SmartManufacturing

Smart Manufacturing and Logistics

2013-2015

SmartGrids

Smart Grids

2013-2015

Dynamics

Dynamics and Applications

2012-2015

e-Policy

Engineering for the Policy-making Life Cycle (ePolicy)

2011-2014

SIMULESP

Expert system to support network operator on real time decision

2011-2015

CRN

Trust-aware Automatic E-Contract Negotiation in Agent-based Adaptive Normative Environments

2010-2013

KDUS

Knowledge Discovery from Ubiquitous Data Streams

2010-2013

Palco3.0

Intelligent Web system to support the management of a social network on music

2008-2011

Argos

Wind power forecasting system

2008-2012

MOREWAQ

Monitoring and Forecasting of Water Quality Parameters

2008-2011

ORANKI

Resource-bounded outlier detection

2008-2011

Team
Publications

LIAAD Publications

View all Publications

2022

Intelligent Monitoring and Management Platform for the Prevention of Olive Pests and Diseases, Including IoT with Sensing, Georeferencing and Image Acquisition Capabilities Through Computer Vision

Authors
Alves A.; Jorge Morais A.; Filipe V.; Alberto Pereira J.;

Publication
Lecture Notes in Networks and Systems

Abstract
Climate change affects global temperature and precipitation patterns. These effects, in turn, influence the intensity and, in some cases, the frequency of extreme environmental events, such as forest fires, hurricanes, heat waves, floods, droughts, and storms. In general, these events can be particularly conducive to the appearance of plant pests and diseases. The availability of models and a data collection system is crucial to manage pests and diseases in sustainable agricultural ecosystems. Agricultural ecosystems are known to be complex, multivariable, and unpredictable. It is important to anticipate crop pests and diseases in order to improve its control in a more ecological and economical way (e.g., precision in the use of pesticides). The development of an intelligent monitoring and management platform for the prevention of pests and diseases in olive groves at Trás-os- Montes region will be very beneficial. This platform must: a) integrate data from multiple data sources such as sensory data (e.g., temperature), biological observations (e.g., insect counts), georeferenced data (e.g., altitude) or digital images (e.g., plant images); b) systematize these data into a regional repository; c) provide relevant forecasts for pest and diseases. Convolutional Neural Networks (CNNs) can be a valuable tool for the identification and classification of images acquired by Internet of Things (IoT).

2022

Host-based IDS: A review and open issues of an anomaly detection system in IoT

Authors
Martins, I; Resende, JS; Sousa, PR; Silva, S; Antunes, L; Gama, J;

Publication
Future Generation Computer Systems

Abstract

2022

MigraR: An open-source, R-based application for analysis and quantification of cell migration parameters

Authors
Shaji, N; Nunes, F; Rocha, MI; Gomes, EF; Castro, H;

Publication
Computer Methods and Programs in Biomedicine

Abstract
Background and objective: Cell migration is essential for many biological phenomena with direct impact on human health and disease. One conventional approach to study cell migration involves the quantitative analysis of individual cell trajectories recorded by time-lapse video microscopy. Dedicated software tools exist to assist the automated or semi-automated tracking of cells and translate these into coordinate positions along time. However, cell biologists usually bump into the difficulty of plotting and computing these data sets into biologically meaningful figures and metrics. Methods: This report describes MigraR, an intuitive graphical user interface executed from the RStudioTM (via the R package Shiny), which greatly simplifies the task of translating coordinate positions of moving cells into measurable parameters of cell migration (velocity, straightness, and direction of movement), as well as of plotting cell trajectories and migration metrics. One innovative function of this interface is that it allows users to refine their data sets by setting limits based on time, velocity and straightness. Results: MigraR was tested on different data to assess its applicability. Intended users of MigraR are cell biologists with no prior knowledge of data analysis, seeking to accelerate the quantification and visualization of cell migration data sets delivered in the format of Excel files by available cell-tracking software. Conclusions: Through the graphics it provides, MigraR is an useful tool for the analysis of migration parameters and cellular trajectories. Since its source code is open, it can be subject of refinement by expert users to best suit the needs of other researchers. It is available at GitHub and can be easily reproduced. © 2021 Elsevier B.V.

2022

Approaches to manage and understand student engagement in programming

Authors
Tavares, PC; Gomes, EF; Henriques, PR; Vieira, DM;

Publication
Open Education Studies

Abstract
Abstract Computer Programming Learners usually fail to get approved in introductory courses because solving problems using computers is a complex task. The most important reason for that failure is concerned with motivation; motivation strongly impacts on the learning process. In this paper we discuss how techniques like program animation, and automatic evaluation can be combined to help the teacher in Computer Programming courses. In the article, PEP system will be introduced to explain how it supports teachers in classroom and how it engages students on study sessions outside the classroom. To support that work, students’ motivation was studied; to complement that study, a survey involving students attending the first year of Algorithms and Programming course of an Engineering degree was done. It is also presented a tool to analyse surveys, using association rules.

2022

LMMS reloaded: Transformer-based sense embeddings for disambiguation and beyond

Authors
Loureiro, D; Mário Jorge, A; Camacho Collados, J;

Publication
Artificial Intelligence

Abstract

Supervised Theses

2021

Barreiras à Exportação: Sector das Rochas Ornamentais

Author
Ana Isabel Mota da Silva

Institution
UP-FEP

2021

Development of differential optrodes for highly sensitive and reliable chemical sensing

Author
João Pedro Sampaio Mendes

Institution
UP-FCUP

2021

WalkingPAD - Smart sensing

Author
Bruno Miguel Ribeiro Pinto

Institution
UP-FCUP

2021

Anomaly Detection for troubleshooting on Cork Stopper sorting Machines

Author
Inês Santos Pereira

Institution
UP-FEUP

2021

Exploring Paraconsistent Logics for Quantum Programs

Author
Ana Luzia Rosa da Cruz

Institution
UM

Facts & Figures

19Papers in indexed journals

2020

29Senior Researchers

2016

23Academic Staff

2020