AUTOML for Data Streams

by Prof. João Gama

Wednesday 8 Oct 2025, 15:30 → 17:00 Europe/Zurich

JvF25/3-303 - Conference Room (Lamarr/RC Trust Dortmund)

Abstract - Learning from data streams is a hot topic in machine learning and data mining. In this talk, we present one of the first algorithms for online hyper-parameter tuning for streaming data. The Self Hyper-Parameter Tuning (SPT) algorithm is an optimisation algorithm for online hyper-parameter tuning from non-stationary data streams. SPT works as a wrapper over any streaming algorithm and can be utilised for classification, regression, and recommendation tasks.

About the speaker - Prof. Dr. João Gama

Bio - 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 EurAI Fellow, IEEE Fellow, and the Asia-Pacific AI Association Fellow. He is a member of the board of directors of the LIAAD, a group belonging to INESC Tec. His main contributions are learning from data streams, where he has an extensive list of publications.  He is the Editor-in-Chief of the International Journal of Data Science and Analytics, published by Springer.