Talk: Advanced topics in data stream mining. Hyper-parameter tunning from data streams; Learning and forgetting: a case study in fraud detection, Real-time failure detection.
João Gama is a Full Professor at the School of Economics, University of Porto, Portugal. He received his Ph.D. in Computer Science from the University of Porto in 2000. He is EurIA Fellow, IEEE Fellow, and member of the board of directors of the LIAAD, a group belonging to INESC TEC. His h-index at Google Scholar is 58. He is an Editor of several top-level Machine Learning and Data Mining journals. He has been ACM Distinguish Speaker. He served as Program Chair of ECMLPKDD 2005, DS09, ADMA09, EPIA 2017, DSAA 2017, served as Conference Chair of IDA 2011, ECMLPKDD 2015, DSAA’2021, and a series of Workshops on KDDS and Knowledge Discovery from Sensor Data with ACM SIGKDD. His main research interests are in knowledge discovery from data streams, evolving data, probabilistic reasoning, and causality. He published more than 300 reviewed papers in journals and major conferences. He has an extensive list of publications in data stream learning.