Searching and learning from sequential data
Speaker: Panagiotis Papapetrou, Professor of Computer Science at the Department of Computer and Systems Sciences at Stockholm University and Adjunct Professor at the Computer Science Department at Aalto University.
Title: Searching and learning from sequential data
In many domains, repeated measurements are collected in order to obtain characteristics of objects or situations that evolve over time. Examples of such domains include shape outline recognition, e.g., for classifying historical documents or projectile points, classification of electrocardiograms (ECGs), and anomaly detection in streaming data. These measurements are typically collected at a fixed rate and such collections are commonly referred to as data series. In this talk I will present some methods for indexing time series data sets hence enabling efficient nearest neighbor search. Moreover, I will discuss techniques for time series feature extraction and classification, as well as techniques for classification of more complex sequences involving events occurring over temporal intervals. The application domains of interest will be ECG classification, sign language recognition, and temporal abstractions of electronic health records.
Bio Dr. Panagiotis Papapetrou is Professor of Computer Science at the Department of Computer and Systems Sciences at Stockholm University and Adjunct Professor at the Computer Science Department at Aalto University. His area of expertise is algorithmic data mining with particular focus on mining and indexing sequential data, complex metric and non-metric spaces, biological sequences, time series, and sequences of temporal intervals. Panagiotis received his PhD in Computer Science at Boston University in 2009, was a post-doctoral researcher at Aalto University during 2009-2013, and lecturer at the University of London during 2012-2013. He has participated in several EU Projects, NSF grants, and Academy of Finland centers of excellence. He also holds a starting grant (Etableringsbidrag) from the Swedish Research Council. He has served as general chair of the 15th International Symposium on Intelligent Data Analysis (IDA) 2016, has participated in the co-organization of three Workshops in the area of Data Mining and Knowledge Discovery, and board member of the Swedish AI Society. He is Associate Editor for the Journal of Data Mining and Knowledge Discovery.