Research Interests
My name is Mathieu Guillame-Bert, and I am working in Google Zurich, Switzerland.
I did my Postdoctoral at CMU (Carnegie Mellon University) in the Auton-Lab (part of Robotic Institute) under the
supervision of Artur Dubrawski. I studied the use of rule extraction and decision
forest-like techniques for symbolic and numerical time series. Typical
applications include Automated and/or assisted Medical Diagnostics, Medical Forecasting,
Human Activity Recognition and Forecasting, Banking Activity Patterns, Fault Detection
and Prediction on complex systems, automatic Foreign exchange market trading, and a bit of Robotics.
I defended my PhD in France in 2012 at the INRIA Research Lab in the PRIMA team under the supervision of James L. Crowley. I studied
the automated extraction of patterns from large temporal datasets, as well as the use of those models for automated prediction, user interpretation and automated reasoning.
I graduate from the Master of Advance Computing of the Imperial College of London, and from the "French Grande Ecole" ENSIMAG (Ecole Nationale Supérieure d'Informatique et de Mathématiques Appliquées) in 2009.

Publications
2018
Article
2017
Journals/Conference Proceedings
2016
Journals/Conference Proceedings
Article
Tutorial
2015
Presentation
2014
Workshop
Presentation
2013
Presentation
Tutorial
2012
Journals/Conference Proceedings
Presentation
Report
2011
Journals/Conference Proceedings
2010
Journals/Conference Proceedings
Prior to 2010
Report
▲ Come back to index
Curriculum vitae
▲ Come back to index
Softwares & Datasets
Click on this link bellow to see the softwares and the data-sets that I created or processed.
Softwares
- TITAR Learner
TITAR (Temporal Interval Tree Association Rule Learner) is Temporal Data Mining algorithm able to extract temporal patterns from symbolic time series and time sequences. These patterns can then be used to user interpretation or for automatic forecasting.
- Event Viewer
A powerful Time Sequences visualier. Event Viewer has been developed during the study of several real world problems. For that reason Event Viewer has a lot of unique features which allow a powerful understanding of data.
- Event Script
Event script is a small but high level flow-oriented declarative programming language designed to facilitate the pre/post processing and the analysis of symbolic and numerical time series and sequences datasets.
- Machine Learning Lab.
A small exploratory tool designed to test and experiment easily with several Machine Learning algorithms on several real work and sythetic datasets.
Public datasets
▲ Come back to index
Gallery
This sections shows some of the nice pictures that I have generated through my research work.
You can click on the picture to get the full size versions.
Learning 3d ellipse with k-nearest neighbor (KNN)
Learning 3d ellipse with AdaBoost
Instance of prediction of bathroom's use
Forex pre-processing console
A* search algorithm in 3D
Screen shot of our game called Build & Defend
TITARL web interface
Ripr linear separation
Cloud of "good" temporal association rules
You can see more of those pictures at the gallery page.
▲ Come back to index
Personal area
See the Personal Area page.
▲ Come back to index