|Assistant HES, PhD student CS UNIGE
Yoann Boget joined the Data Mining and Machine Learning group in the Department of Business Informatics of the University of Applied Sciences-Western Switzerland, in April 2020 as research assistant. After having been working as social scientist, he studied statistics in University of Neuchâtel. He wrote his Master on Adversarial Regression as intern at the SLAC National Laboratory, Stanford University, under the supervision of Michael Kagan. He collaborated with CERN OpenLab on the project Deep Learning for Satellite Imagery.
His main field of research consist of investigating deep generative models with incorporation of domain knowledge. Specifically, He focuses on VAEs- and GANs-based algorithm to generate discrete data. As field of experiment, he is currently working on de novo drug generation.
He is also part of the IAI -Innosuisse project, working on industrial Artificial Intelligence for intelligent machines and manufacturing digitalization. He is developing deep learning algorithm for predictive maintenance.
Adversarial Regression. Generative Adversarial Networks for Non-Linear Regression: Theory and Assessment , University of Neuchâtel, Master Thesis, under the supervison of Michael Kagen (Stanford University), 2019, GPA 5.5/6.