Mathieu Guillame-Bert

Mathieu Guillame-Bert has extensive experience in research and engineering, particularly in the fields of machine learning, data mining, and time series analysis. At Carnegie Mellon University, Mathieu served as a Post Doctoral Fellow focusing on model extraction for classification in non-synchronized multivariate time series, with applications in forecasting cardio-respiratory issues for intensive care patients. Prior roles include Junior Project Scientist, where Mathieu managed research projects, and Engineer Student at Datechsys, specializing in GPS and MEMS sensor hybridization. Additionally, Mathieu engaged in a significant MSc research project at Imperial College London concerning first-order logic learning in neural networks, which led to a publication. A PhD in Mathematics and Computer Science was obtained at INRIA, involving the study of temporal association rules. Currently, Mathieu is a Research Engineer at Google since September 2016. Educational background includes preparatory classes in Physics, Engineering, and Mathematics at Déodat de Séverac and an MSc in Advanced Computing from Imperial College London.