About

Carl Johann Simon-Gabriel is a highly skilled Machine Learning Researcher at Amazon Web Services with a passion for developing methods to enhance the robustness of deep networks for image analysis. He is particularly interested in exploring problems related to adversarial robustness, out-of-distribution predictions, and causal learning on images. With over 3 years of relevant experience, Carl has worked on kernel methods and computational biology methods in the past, further expanding his expertise in the field. Carl's current role as an Applied Scientist at Amazon has enabled him to continue his work on adversarial examples while exploring the connections between causality, adversarial learning, and reinforcement learning. Prior to joining Amazon, Carl was a Postdoctoral Researcher at ETH Zürich, where he worked in the Learning and Adaptive Systems group led by Prof. Andreas Krause. During his time at ETH Zürich, Carl focused on adversarial examples and planned to continue this work while exploring the links between causality, adversarial learning, and reinforcement learning. Carl's previous experience also includes a Research Internship at Facebook AI, where he worked with Yann Ollivier, Léon Bottou, and David Lopez-Paz to understand the origin of adversarial vulnerability in state-of-the-art convolutional network classifiers. Carl's academic background includes a Ph.D. in Machine Learning from the Max Planck Society, a Master's in General Engineering from Mines Paris, and a Diploma in Music Studies from the Conservatoire de Strasbourg. Carl's technical skills include expertise in Research Science, Machine Learning, Web Development, AWS, AI, and Reinforcement Learning. Carl is a highly motivated and results-driven individual with a passion for solving complex problems in the field of machine learning.