Robert West

Robert West is an Associate Professor of computer science at EPFL, where he heads the Data Science & AI Lab (dlab). His research lies at the intersection of artificial intelligence (AI), natural language processing (NLP), and computational social science (CSS), with a focus on building AI that is safe for humanity. Bob received his PhD in Computer Science from Stanford University (2016), his MSc from McGill University (2010), and his undergraduate degree from Technische Universität München (2007). He is an ELLIS Scholar, a Wikimedia Foundation Research Fellow, an Associate Editor and AI Column Head of the Communications of the ACM, an Associate Editor of ICWSM and EPJ Data Science, and a co-founder of the Wiki Workshop and the Applied Machine Learning Days. In 2024/2025, Bob spent a sabbatical as a Visiting Researcher with Microsoft Research Redmond, where he worked on agentic AI with the AI Frontiers team. His work has won several awards, including best/outstanding paper awards and honorable mentions at NAACL 2025, ACL 2024, CSCW 2021 & 2025, ICWSM 2019 & 2021 & 2024 & 2025, and WWW 2013 & 2016, a Google Faculty Research Award, a Facebook Research Award, and the ICWSM 2022 Adamic–Glance Distinguished Young Researcher Award. Teaching & PhD PhD Students Tim Ruben Davidson, Ivan Zakazov, Saibo Geng, Mohammad Hossein Amani Past EPFL PhD Students Tiziano Piccardi, Kristina Gligoric, Akhil Arora, Lars Henning Klein, Valentin Hartmann, Manoel Horta Ribeiro, Martin Josifoski, Marija Sakota Past EPFL PhD Students as codirector Ramtin Yazdanian 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. Machine learning CS-433 Machine learning methods are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and practically implemented. Topics in Computational Social Science (TopiCSS) CS-727 This is a seminar course. By reading and discussing an introductory book as well as research papers about computational social science, students will become familiar with core issues and techniques in the field. Awards Google Faculty Research Award 2017 Google 2017 ICWSM Adamic-Glance Distinguished Young Researcher Award International Conference on Web and Social Media 2023