Germain Forestier: Deep Learning for Time Series Classification

calendar icon

Event Details

7th Nov 2018 2:00pm-3:00pm
Clayton Seminar Room G12A, 14 Rainforest Walk, Video Conference to H7.84 Caulfield
IT research seminars


Speaker: Germain Forestier (Univ. of Haute-Alsace, IRIMAS, France)


Germain Forestier

In recent years, deep learning approaches have demonstrated a tremendous success in multiple domains like image processing, computer vision or speech recognition. In this talk, I will review recent advances in deep learning for univariate and multivariate time series classification. I will present experimental results obtained with the principal architectures proposed in the literature. I will also discuss the main challenges linked with the use of deep learning like transfer learning and data augmentation. Finally, I will present some applications in the field of Surgical Data Science which is an emerging field with the objective of improving the quality of interventional healthcare through capturing, organizing, analyzing, and modeling of data.

Presenter bio

Prof Germain Forestier received his PhD in Computer Science from the University of Strasbourg in 2010. He then spent one year as a postdoctoral fellow at INRIA Rennes / INSERM (French National Institute for Medical and Health Research), where he worked on biomedical data analysis. In September 2011, he obtained a position of Associate Professor at the University of Haute-Alsace (France) and is now Professor since 2018. Prof Forestier also hold a position of Senior Lecturer (Adjunct) at the Monash University (Australia). His research interests include data science, data mining, time series, machine learning, big data, artificial intelligence and deep learning.

More info:

Host: François Petitjean

Tea, coffee, and snacks will be available at the primary venue for the audience after the talk.

Event Contact

François Petitjean