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Adelaide Cerveira

Adelaide Cerveira

 

 

Adelaide Cerveira received the B.Sc. degree in Mathematics- Operations Research branch from the University of Coimbra, Coimbra, Portugal, in 1993, the M.Sc. degree in Operations Research from the University of Lisbon, Lisbon, Portugal, in 1998, and the Ph.D. degree in Statistics and Operations Research from the University of Lisbon, Lisbon, Portugal, in 2006.

 

She is currently an Auxiliary Professor in Mathematics Department of Science and Technology School with UTAD.

 

Her current research interests include combinatorial optimization and applications, especially on forest management and Network Design. Her past research also includes Semidefinite Programming and applications to Structural Design.

 

 

Domains

Artificial IntelligencePower and Energy Systems

Publications

Advancing Renewable Energy Forecasting: A Comprehensive Review of Renewable Energy Forecasting Methods

Teixeira, R;Cerveira, A;Pires, EJS;Baptista, J;

2024

ENERGIES

Enhancing Weather Forecasting Integrating LSTM and GA

Teixeira, R;Cerveira, A;Pires, EJS;Baptista, J;

2024

APPLIED SCIENCES-BASEL

Optimal Location of Electric Vehicle Charging Stations in Distribution Grids Using Genetic Algorithms

Gomes, E;Cerveira, A;Baptista, J;

2024

OPTIMIZATION, LEARNING ALGORITHMS AND APPLICATIONS, PT I, OL2A 2023

Impact of Electric Vehicle Charging Stations on Distribution Grids with PV Integration

Silva, P;Cerveira, A;Baptista, J;

2023

International Conference on Electrical, Computer and Energy Technologies, ICECET 2023

View all publications

Supervised Theses

Provenance Control and Auditability in Autonomous Driving

Sérgio Paulo de Sousa Moreira Neto

M - 2024

UP-FCUP

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.

Artificial Intelligence and Decision Support

Information and Contacts

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