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Administrative data

Antoine Bosselut

antoine.bosselut@epfl.ch +41 21 693 62 13 https://atcbosselut.github.io

EPFL IC IINFCOM NLP
INR 234 (Bâtiment INR)
Station 14
1015 Lausanne

EPFL IC-DO
INR 234 (Bâtiment INR )
Station 14
1015 Lausanne

EPFL IC-DO
INR 234 (Bâtiment INR )
Station 14
1015 Lausanne

EPFL IC-DO
INR 234 (Bâtiment INR )
Station 14
1015 Lausanne

EPFL IC-DO
INR 234 (Bâtiment INR )
Station 14
1015 Lausanne

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.

Awards

ELLIS Scholar

ELLIS

2024

AI2050 Early Career Fellowship

Schimdt Sciences

2025

ERC Starting Grant

ERC

2025

Teaching & PhD

PhD Students

Sepideh Mamooler, Badr Alkhamissy, Silin Gao, Auguste Poiroux, Beatriz Borges, Molly Rose Petersen, Madhur Panwar, Zeming Chen, Mahammad Ismayilzada, Ayush Kumar Tarun, Deniz Bayazit, Angelika Romanou

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.