Carlos Manuel Milheiro de Oliveira Pinto Soares

Domains

Artificial Intelligence and Decision Support

Projects

Chatbot_Intelligence

opti-MOVES

The project combined diagnosis and optimization methods to improve the quality of urban public transport, particularly intermodal transport services. The system aims to support decisionmaking of mobility operators and authorities, in planning, monitoring and optimizing intermodal operations and in the definition of urban policies. Positive impacts are expected, with an increase of public transport utilization, and a reduction of energy costs and pollutant emissions.

Quality management of intermodal public transport services: diagnosis and optimization

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Publications

RHiOTS: A Framework for Evaluating Hierarchical Time Series Forecasting Algorithms

Roque, L;Soares, C;Torgo, L;

2024

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2024, Barcelona, Spain, August 25-29, 2024

Machine Learning Data Market Based on Multiagent Systems

Baghcheband, H;Soares, C;Reis, LP;

2024

IEEE INTERNET COMPUTING

Corrector LSTM: built-in training data correction for improved time-series forecasting

Baghoussi, Y;Soares, C;Moreira, JM;

2024

Neural Comput. Appl.

Shapley-Based Data Valuation Method for the Machine Learning Data Markets (MLDM)

Baghcheband, H;Soares, C;Reis, LP;

2024

FOUNDATIONS OF INTELLIGENT SYSTEMS, ISMIS 2024

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Supervised theses

Study and development of optical fiber structures based on graphene

Catarina da Silva Monteiro

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.