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About

João Gama is Associate Professor of 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 Senior member of IEEE.

He has worked in 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, and ECML/PKDD'2015. 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 author of several books in 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.

Interest
Topics
Details

Details

  • Name

    João Gama
  • Cluster

    Computer Science
  • Role

    Research Coordinator
  • Since

    01st April 2009
018
Publications

2022

Host-based IDS: A review and open issues of an anomaly detection system in IoT

Authors
Martins, I; Resende, JS; Sousa, PR; Silva, S; Antunes, L; Gama, J;

Publication
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE

Abstract

2022

A Fault Detection Framework Based on LSTM Autoencoder: A Case Study for Volvo Bus Data Set

Authors
Davari, N; Pashami, S; Veloso, B; Nowaczyk, S; Fan, Y; Pereira, PM; Ribeiro, RP; Gama, J;

Publication
Advances in Intelligent Data Analysis XX - 20th International Symposium on Intelligent Data Analysis, IDA 2022, Rennes, France, April 20-22, 2022, Proceedings

Abstract

2022

Bank Statements to Network Features: Extracting Features Out of Time Series Using Visibility Graph

Authors
Shaji, N; Gama, J; Ribeiro, RP; Gomes, P;

Publication
Advances in Intelligent Data Analysis XX - 20th International Symposium on Intelligent Data Analysis, IDA 2022, Rennes, France, April 20-22, 2022, Proceedings

Abstract
Non-traditional data like the applicant’s bank statement is a significant source for decision-making when granting loans. We find that we can use methods from network science on the applicant’s bank statements to convert inherent cash flow characteristics to predictors for default prediction in a credit scoring or credit risk assessment model. First, the credit cash flow is extracted from a bank statement and later converted into a visibility graph or network. Afterwards, we use this visibility network to find features that predict the borrowers’ repayment behaviour. We see that feature selection methods select all the five extracted features. Finally, SMOTE is used to balance the training data. The model using the features from the network and the standard features together is shown having superior performance compared to the model that uses only the standard features, indicating the network features’ predictive power. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

2022

Data-driven Predictive Maintenance

Authors
Gama, J; Ribeiro, RP; Veloso, B;

Publication
IEEE Intelligent Systems

Abstract

2022

Advances in Knowledge Discovery and Data Mining - 26th Pacific-Asia Conference, PAKDD 2022, Chengdu, China, May 16-19, 2022, Proceedings, Part I

Authors
Gama, J; Li, T; Yu, Y; Chen, E; Zheng, Y; Teng, F;

Publication
PAKDD (1)

Abstract

Supervised
thesis

2021

Design and construction of cost effective VTOL drone for agricultural and forestry application

Author
Ahmad Safaee

Institution
UP-FEUP

2021

Multicriteria evaluation as a tool for decision support in the design of sustainable routes

Author
Joana Sofia Campos Santos

Institution
UP-FEUP

2021

AutoFITS: Automated feature engineering for irregular time-series

Author
Pedro Miguel Pinto Costa

Institution
UP-FCUP

2021

Lean Management and Industry 4.0: integration’s critical factors and their impact on performance

Author
Marta Filipa Moreira Vaz

Institution
UP-FEP

2021

Segmentação fonética adaptativa em voz disfónica

Author
João Filipe Torres Costa

Institution
UP-FEUP