Pedro Campos

Domains

Artificial Intelligence and Decision Support Artificial Intelligence

Projects

NEXT-NET

NEXT-NET project creates a cross-sectoral initiative at European level to increase integration between production and distribution, proposing research and innovation priorities for the future of supply chains.

Next generation Technologies for networked Europe

HALM

Publications

Data Science, Statistics, and Civic Statistics: Education for a Fast Changing World

Ridgway, J;Campos, P;Biehler, R;

2023

Statistics for Empowerment and Social Engagement: Teaching Civic Statistics to Develop Informed Citizens

Project-Based Learning with a Social Impact: Connecting Data Science Movements, Civic Statistics, and Service-Learning

Zejnilovic, L;Campos, P;

2023

Statistics for Empowerment and Social Engagement: Teaching Civic Statistics to Develop Informed Citizens

Exploring Climate Change Data with R

Guimarães, N;Vehkalahti, K;Campos, P;Engel, J;

2023

Statistics for Empowerment and Social Engagement: Teaching Civic Statistics to Develop Informed Citizens

Data Sets: Examples and Access for Civic Statistics

Teixeira, S;Campos, P;Trostianitser, A;

2023

Statistics for Empowerment and Social Engagement: Teaching Civic Statistics to Develop Informed Citizens

View all publications

Supervised theses

Distributed query processing in dataspaces

João Pedro Araújo Parente

D - 2023

UM-EEUM

Centres

Artificial Intelligence and Decision Support

Our Laboratory of Artificial Intelligence and Decision Support (LIAAD) conducts research in the fields of Artificial Intelligence, Machine Learning, Data Science, and Modelling. These areas are cross-cutting and apply to all sectors of society and the economy. The vast amounts of data being collected, alongside the ubiquity of digitalisation and sensorisation, are increasingly creating opportunities and challenges for automating decision support. The combination of Machine Learning and complex models is transforming the economy, healthcare, justice, industry, science, public administration, and education. This encourages us to invest in diverse technological and scientific approaches and perspectives. Our overarching strategy is to explore the flow and diversification of data, and to invest in research lines that will lead to the development of applied Artificial Intelligence foundations and models that are responsible and human centred.