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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 won third place at the Arquivo.pt Award

Ricardo Campos, researcher at INESC TEC and professor at the Polytechnic Institute of Tomar, together with Diogo Correia, was one of the winners of the Arquivo.pt Award. The duo won the third place and an honourable mention by the newspaper Público, thanks to the project Arquivo Público, a web interface focused on the contents published on the newspaper's website over time, and preserved by Arquivo.pt.

05th December 2022

Computer Science

INESC TEC researcher leads one of the finalist teams of the European Innovation Academy

Tiago Neves, an INESC TEC researcher, is the team leader of “MetaFitGame”, one of the 10 contender start-ups of the European Innovation Academy (EIA) 2022. “MetaFitGame” is a mobile fitness app that aims to encourage people to practice sports in a fun way, transforming physical exercises into a game.

27th September 2022

Computer Science

New book on Artificial Intelligence authored by INESC TEC

"Metalearning: Applications to Automated Machine Learning and Data Mining" is the title of the new book by Pavel Brazdil and Carlos Soares, researchers at INESC TEC, written in partnership with Jan N. van Rijn and Joaquin Vanschoren.

29th August 2022

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

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Featured Projects

Produtech R3

Agenda Mobilizadora da Fileira das Tecnologias de Produção para a Reindustrialização

2022-2025

ADANET

Internet das Coisas Assistida por Drones

2022-2025

PFAI4_3ed

Programa de Formação Avançada Industria 4 - 3a edição

2022-2022

FORM_I40

Formação Indústria 4.0

2022-2022

DAnon

Supervised Deanonymization of Dark Web Traffic for Cybercrime Investigation

2022-2023

THEIA

Automated Perception Driving

2022-2023

City Analyser

An agnostic platform to analyse massive mobility patterns

2021-2023

HfPT

Health from Portugal

2021-2025

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

SIGIPRO

Sistema inteligente de gestão de processos habilitados espacialmente

2021-2023

DigitalBudget_VE

Aplicação computacional para orçamentação automática de postos de carregamento de VE

2021-2021

XPM

eXplainable Predictive Maintenance

2021-2024

SSPM

Student Success Prediction Model

2021-2022

OnlineAIOps

Online Artificial Intelligence for IT Operations

2021-2023

AI_Sov

AI Sovereignty

2021-2021

CloudAnalytics4Dams

Gestão de Grandes Quantidades de Dados em Barragens da EDP Produção

2021-2021

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

2020-2024

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

2020-2023

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

2019-2023

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

2019-2023

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

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

MaLPIS

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

2018-2022

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

Simulation, modelling and classification of wiki contributors: Spotting the good, the bad, and the ugly

Authors
Garcia-Mendez, S; Leal, F; Malheiro, B; Burguillo-Rial, JC; Veloso, B; Chis, AE; Gonzalez-Velez, H;

Publication
SIMULATION MODELLING PRACTICE AND THEORY

Abstract

2022

The MetroPT dataset for predictive maintenance

Authors
Veloso, B; Ribeiro, RP; Gama, J; Pereira, PM;

Publication
SCIENTIFIC DATA

Abstract
AbstractThe paper describes the MetroPT data set, an outcome of a Predictive Maintenance project with an urban metro public transportation service in Porto, Portugal. The data was collected in 2022 to develop machine learning methods for online anomaly detection and failure prediction. Several analog sensor signals (pressure, temperature, current consumption), digital signals (control signals, discrete signals), and GPS information (latitude, longitude, and speed) provide a framework that can be easily used and help the development of new machine learning methods. This dataset contains some interesting characteristics and can be a good benchmark for predictive maintenance models.

2022

The spatial distribution and biogeochemical drivers of nitrogen cycle genes in an Antarctic desert

Authors
Pascoal, F; Areosa, I; Torgo, L; Branco, P; Baptista, MS; Lee, CK; Cary, SC; Magalhaes, C;

Publication
FRONTIERS IN MICROBIOLOGY

Abstract
Antarctic deserts, such as the McMurdo Dry Valleys (MDV), represent extremely cold and dry environments. Consequently, MDV are suitable for studying the environment limits on the cycling of key elements that are necessary for life, like nitrogen. The spatial distribution and biogeochemical drivers of nitrogen-cycling pathways remain elusive in the Antarctic deserts because most studies focus on specific nitrogen-cycling genes and/or organisms. In this study, we analyzed metagenome and relevant environmental data of 32 MDV soils to generate a complete picture of the nitrogen-cycling potential in MDV microbial communities and advance our knowledge of the complexity and distribution of nitrogen biogeochemistry in these harsh environments. We found evidence of nitrogen-cycling genes potentially capable of fully oxidizing and reducing molecular nitrogen, despite the inhospitable conditions of MDV. Strong positive correlations were identified between genes involved in nitrogen cycling. Clear relationships between nitrogen-cycling pathways and environmental parameters also indicate abiotic and biotic variables, like pH, water availability, and biological complexity that collectively impose limits on the distribution of nitrogen-cycling genes. Accordingly, the spatial distribution of nitrogen-cycling genes was more concentrated near the lakes and glaciers. Association rules revealed non-linear correlations between complex combinations of environmental variables and nitrogen-cycling genes. Association rules for the presence of denitrification genes presented a distinct combination of environmental variables from the remaining nitrogen-cycling genes. This study contributes to an integrative picture of the nitrogen-cycling potential in MDV.

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

Smart Contracts for the CloudAnchor Platform

Authors
Vasco, E; Veloso, B; Malheiro, B;

Publication
Advances in Practical Applications of Agents, Multi-Agent Systems, and Complex Systems Simulation. The PAAMS Collection - 20th International Conference, PAAMS 2022, L'Aquila, Italy, July 13-15, 2022, Proceedings

Abstract

Supervised Theses

2021

Anomaly Detection for troubleshooting on Cork Stopper sorting Machines

Author
Inês Santos Pereira

Institution
UP-FEUP

2021

Desenvolvimento de soluções energeticamente sustentáveis para ginásios

Author
Nuno Henrique Gaspar Pacheco

Institution
UTAD

2021

Previsão de compras através de link prediction em redes bipartidas e unipartidas o caso prático da Amazon

Author
Inês Silva Fernandes

Institution
UP-FEP

2021

Monitoring and Real-time Simulation of an Industrial Production Pipeline

Author
José Diogo Lago Viana

Institution
UM

2021

eIDAS Qualified Trust Services - Serviço de preservação

Author
João Manuel da Silva Fernandes

Institution
UM

Facts & Figures

19Papers in indexed journals

2020

29Senior Researchers

2016

3Book Chapters

2020