Antoine Bosselut

Expertise Natural Language Processing (NLP), Artificial Intelligence (AI), Machine Learning (ML) Antoine Bosselut is an assistant professor at EPFL. He leads the EPFL NLP group, which conducts research on natural language processing (NLP) systems that can model, represent, and reason about human and world knowledge.Prior to joining EPFL, he was a postdoctoral researcher at Stanford University working in the SNAP and NLP groups and a young investigator on the Mosaic project at the Allen Institute for AI. He completed his PhD at the University of Washington. Teaching & PhD PhD Students Sepideh Mamooler, Badr Alkhamissy, Auguste Poiroux, Beatriz Borges, Molly Rose Petersen, Madhur Panwar, Zeming Chen, Mahammad Ismayilzada, Ayush Kumar Tarun, Deniz Bayazit, Angelika Romanou, Maria Grandury Past EPFL PhD Students Silin Gao Past EPFL PhD Students as codirector Shaobo Cui, Li Mi, Negar Foroutan Eghlidi Courses EECS Seminar: Advanced Topics in Machine Learning ENG-704 Students learn about advanced topics in machine learning, artificial intelligence, optimization, and data science. Students also learn to interact with scientific work, analyze and understand strengths and weaknesses of scientific arguments of both theoretical and experimental results. Introduction to natural language processing CS-431 The objective of this course is to present the main models, formalisms and algorithms necessary for the development of applications in the field of natural language information processing. The concepts introduced during the lectures will be applied during practical sessions. Modern natural language processing CS-552 Natural language processing is ubiquitous in modern intelligent technologies, serving as a foundation for language translators, virtual assistants, search engines, and many more. In this course, students will learn algorithmic tools for tackling problems in modern NLP. Topics in Natural Language Processing CS-612 This seminar course explores advanced topics in natural language processing through a mix of reading, reviewing, and writing academic papers. Awards ELLIS Scholar ELLIS 2024 AI2050 Early Career Fellowship Schmidt Sciences 2025 ERC Starting Grant ERC 2025