Agenda

Prof. Stan Matwin, Institute for Big Data Analytics, Dalhousie University Halifax, Nova Scotia, Canada

Abstract:
In this presentation, we will describe the satellite Automatic Identification System (s-AIS)– a fundamental tool for the analysis and understanding of the mobility of ocean vessels. We will argue that AIS data meets all the Big Data characteristics, and introduce the challenges it presents. We will then present the work at Dalhousie on the use of Machine Learning for several applications of AIS, especially in monitoring and understanding the global fishing activities. We will discuss the full application cycle: the AIS data management challenges and how we addressed them, the research and methodological issues in applying Machine Learning (both supervised and unsupervised) on AIS data, and the AIS visualization opportunities. We will present preliminary results for two fishing-related research projects using spatio-temporal data analytics, Machine Learning and Deep Learning approaches. One of the presented projects is carried out in collaboration with the Ca’Foscari University of Venice in the context of the Marie Curie H2020 RIS program. We will outline some of the exciting data science research opportunities arising from the growing use of AIS system and its data.

Bio Sketch:
Stan Matwin is the Director of the Institute for Big Data Analytics at Dalhousie University, Halifax, Nova Scotia, Canada, where he is a Professor and Canada Research Chair at the Faculty of Computer Science. He is also a Distinguished Professor at the University of Ottawa, State Professor at the Institute of Computer Science of the Polish Academy of Sciences, and a member of the Board of the PhD program at the Scuola Normale Superiore. Stan holds the titles of Fellow of the European Coordinating Committee on AI, and is a Fellow and the Life Time Achievement Award laureate of the Canadian AI Association (CAIAC). Internationally recognized for his work in text mining and in applications of Machine Learning, he is the Area Chair for Applications of the Springer Encyclopedia of Machine Learning. Stan was the General Chair of KDD 2017 in Halifax, Canada. Author and co-author of more than 300 refereed papers, he produced more than 80 Ph.D. and M.Sc. graduates.