
About Project
Perfis para Anomalias Consumo
Acronym
PANACea
Responsible
José Nuno Moura Marques Fidalgo
Status
Closed
Start
January 8, 2016
End
January 30, 2019
Effective End
January 30, 2019
Global Budget
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Financing
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Website
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Members
Team Leaders
José Nuno Fidalgo
Associate Professor since 2011 at the Faculty of Engineering of the University of Porto (FEUP).
PhD obtained in 1995 in Electrical Engineering and Computers at FEUP.
Licenciado in 1984 in Electrical Engineering and Computers at FEUP.
Researcher at INESC TEC since 1985.

João Gama
João Gama is a Full Professor at the Faculty of Economy, University of Porto. He is a researcher and vice-director of LIAAD, a group belonging to INESC TEC. He got the PhD degree from the University of Porto, in 2000. He is a IEEE Fellow and EurIA Fellow.
He has worked on several National and European projects on Incremental and Adaptive learning systems, Ubiquitous Knowledge Discovery, Learning from Massive, and Structured Data, etc. He served as Co-Program chair of ECML'2005, DS'2009, ADMA'2009, IDA' 2011, ECMLPKDD'2015, and ECMLPKDD 2025. He served as track chair on Data Streams with ACM SAC from 2007 till 2016. He organized a series of Workshops on Knowledge Discovery from Data Streams with ECML/PKDD, and Knowledge Discovery from Sensor Data with ACM SIGKDD. He is the author of several books on Data Mining (in Portuguese) and authored a monograph on Knowledge Discovery from Data Streams. He authored more than 250 peer-reviewed papers in areas related to machine learning, data mining, and data streams. He is a member of the editorial board of international journals ML, DMKD, TKDE, IDA, NGC, and KAIS. He (co-)supervised more than 12 PhD students and 50 MSc students.
Associated 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.

Power and Energy Systems
INESC TEC’s main actor in the energy field is the Centre for Power and Energy Systems (CPES), which falls within the Cluster Energy Systems. We at CPES are internationally recognised for our expertise in the integration of renewable energy in power systems, distributed generation, storage, smart grids and areas traditionally associated with the planning and operation of power systems. The high level of expertise developed has allowed our experts at CPES to take on key roles in important EU projects as part of the successive framework programmes that led to notable scientific and technical advances with considerable impact on industry. This has led to contracts for development and consultancy with companies manufacturing equipment and with generation, transmission and distribution companies, regulators, government agencies and investors in Europe, South America, the United States of America and Africa. At CPES, we address the following main research areas: Decision Making, Optimisation and Computational Intelligence, Forecasting, Static and Dynamic analysis of Energy Grids, Reliability, Power Electronics.
