Thomas Gaudelet

Thomas Gaudelet has a diverse work experience, beginning with an internship at EDF in 2013. Following this, they interned at Keio University in 2013, where they investigated the condensation behaviour of water on PTFE-based coating. In 2014, they interned at PathControl, developing the user interface of the software of passive magnetic ranging. In 2016, they held an R&D Intern position at Fuel3D and a Teaching Assistant position at UCL, where they supported modules such as Advanced Deep Learning and Reinforcement Learning, Introduction to Machine Learning, and Robotics Programming. In 2019, they were a Research Student at Stanford University in the SNAP group, working with Prof. Jure Leskovec and Dr. Marinka Zitnik. Currently, they are an Associate Director - Machine Learning Research at Relation Therapeutics.

Thomas Gaudelet's education history includes a Doctor of Philosophy (Ph.D.) in Computer Science from UCL, obtained between 2016 and 2020. Prior to this, they obtained a Master of Science (M.Sc.) in Mathematical Modelling & Scientific Computing from the University of Oxford between 2014 and 2015. Thomas also obtained a Master of Engineering (MEng) in General Engineering from Ecole centrale de Lyon between 2011 and 2016. Additionally, they have obtained certifications in Structuring Machine Learning Projects, Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, and Neural Networks and Deep Learning from Coursera in 2017.