Robert West

Edit profile

Associate Professor

robert.west@epfl.ch +41 21 693 35 36 http://dlab.epfl.ch/people/west/

Google Scholar ID

EPFL IC IINFCOM DLAB
INN 310 (Bâtiment INN)
Station 14
1015 Lausanne

+41 21 693 35 36
+41 21 693 69 67
Office: INN 310
EPFL > IC > IINFCOM > DLAB

+41 21 693 35 36
EPFL > IC > IC-SIN > SIN-ENS

Web site: Web site: https://sin.epfl.ch

+41 21 693 35 36
EPFL > IC > IC-SSC > SSC-ENS

Web site: Web site: https://ssc.epfl.ch

+41 21 693 35 36
EPFL > CDH > CDH-SODH > SODH-ENS

+41 21 693 35 36
EPFL > VPA-AVP-DLE > AVP-DLE-EDOC > EDDH-GE

Web site: Web site: https://go.epfl.ch/phd-eddh

+41 21 693 35 36
EPFL > VPA-AVP-DLE > AVP-DLE-EDOC > EDIC-ENS

+41 21 693 35 36
EPFL > VPA-AVP-DLE > AVP-DLE-EDOC > EDEE-ENS

vCard

Biography

Robert West is a tenure-track assistant professor of computer science at EPFL (the Swiss Federal Institute of Technology, Lausanne), where he heads the Data Science Lab (dlab). His research aims to make sense of large amounts of data by developing and applying algorithms and techniques in natural language processing, machine learning, and computational social science. Typically, the data he works with is generated by humans (e.g., natural language or behavioral traces), and frequently it is collected on the Web (e.g., using wikis, online news, social media, server logs, online games). Bob received his PhD in Computer Science from Stanford University (2016), his MSc from McGill University, Canada (2010), and his undergraduate degree from Technische Universität München, Germany (2007). He is a Wikimedia Foundation Research Fellow, an Associate Editor of ICWSM and EPJ Data Science, and a co-founder of the Wiki Workshop and the Applied Machine Learning Days. His work has won several awards, including best/outstanding paper awards at ICWSM’21, ICWSM’19, and WWW’13, a Google Faculty Research Award, a Facebook Research Award, and the ICWSM’22 Adamic–Glance Distinguished Young Researcher Award.

[Last updated: 23 Feb 2023]

Teaching & PhD

Teaching

Computer Science

Communication Systems
Digital Humanities

PhD Students

Amani Mohammad Hossein, Davidson Tim Ruben, Geng Saibo, Sakota Marija, Zakazov Ivan,

Past EPFL PhD Students

Arora Akhil , Gligoric Kristina , Hartmann Valentin , Horta Ribeiro Manoel , Josifoski Martin , Klein Lars Henning , Piccardi Tiziano , Yazdanian Ramtin ,

Courses

Machine learning

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)

Data collected through digital systems, such as online social networks, search engines, mobile phones, apps, etc., offer great opportunities for addressing important research questions about individual as well as collective human behavior. Whereas such issues had previously been studied primarily by social scientists, the sheer size of modern social data sets, as well as the fact that they are

EECS Seminar: Advanced Topics in Machine Learning

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.