Ana Rita Nogueira

Assistant Researcher

I hold a Ph.D. in Computer Science from the University of Porto and work as a Researcher at INESC TEC. My research focuses on causal discovery and machine learning. I have experience in programming with Python and R, as well as working with REST APIs and databases. At INESC TEC, I am part of a team that develops innovative technological solutions.

Domains

Artificial Intelligence

Projects

FAIST

PAPVI2

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Publications

Lasting brain functional connectivity changes induced by positive emotional stimuli in insomnia patients

Ernesto, SA;Nogueira, AR;Léré, G;Daviaux, Y;Philip, P;Sousa, R;Catheline, G;Altena, E;

2024

JOURNAL OF SLEEP RESEARCH

Causal Reasoning in Data

Nogueira, AR;

2023

Time-Series Pattern Verification in CNC Machining Data

Silva, JM;Nogueira, AR;Pinto, J;Alves, AC;Sousa, R;

2023

PROGRESS IN ARTIFICIAL INTELLIGENCE, EPIA 2023, PT I

KDBI special issue: Time-series pattern verification in CNC turning-A comparative study of one-class and binary classification

da Silva, JP;Nogueira, AR;Pinto, J;Curral, M;Alves, AC;Sousa, R;

2025

EXPERT SYSTEMS

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Supervised Theses

Anomaly Detection on Multivariate Time-Series from Lithography Equipment using Machine Learning

João Gabriel Luís Patrício

M - 2023

UP-FEUP

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.

Information and Contacts

Phone

+351220402963

Email

[email protected]