Robert West

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Tenure Track Assistant 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
CH-1015 Lausanne

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

EPFL IC SIN-GE
INN 310 (Bâtiment INN)
Station 14
CH-1015 Lausanne

+41 21 693 35 36
Office: INN 310
EPFL > IC > IC-SIN > SIN-ENS

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

EPFL IC SSC-GE
INR 130 (Bâtiment INR)
Station 14
CH-1015 Lausanne

+41 21 693 35 36
Office: INR 130
EPFL > IC > IC-SSC > SSC-ENS

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

EPFL CDH SODH-GE
INN 136 (Bâtiment INN)
Station 14
CH-1015 Lausanne

+41 21 693 35 36
Office: INN 136
EPFL > CDH > CDH-SODH > SODH-ENS

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Administrative data

Biography

Robert West is a tenure-track assistant professor of computer science at EPFL, where he heads the Data Science Lab. In his research, he develops and applies techniques in machine learning, computational social science, natural language processing, social network analysis, and data mining. Bob also collaborates closely with the Wikimedia Foundation, in his role as a Wikimedia Research Fellow. Bob’s work has won several awards, including best/outstanding paper awards at ICWSM’21, ICWSM’19, and WWW’13, a best-paper runner-up award at WWW’16, a Google Faculty Research Award, a Facebook Research Award, a Hewlett-Packard Graduate Fellowship, and a Facebook Graduate Fellowship. He is actively involved in the research community, e.g., as an Associate Editor of ICWSM and EPJ Data Science and as a co-founder of the Wiki Workshop (held at WWW and ICWSM) and the Applied Machine Learning Days. Bob received his PhD in Computer Science from Stanford University, his MSc from McGill University, Canada, and his undergraduate degree from Technische Universität München, Germany.

[Last updated: 25 Aug 2021]

Teaching & PhD

Teaching

Computer Science

Communication Systems
Digital Humanities

PhD Programs

Doctoral program in computer and communication sciences

Doctoral Program Digital Humanities

PhD Students

Arora Akhil, Gligoric Kristina, Hartmann Valentin, Horta Ribeiro Manoel, Josifoski Martin, Piccardi Tiziano, Sakota Marija, Yazdanian Ramtin,

Courses

Applied data analysis

This course teaches the basic techniques, methodologies, and practical skills required to draw meaningful insights from a variety of data, with the help of the most acclaimed software tools in the data science world: pandas, scikit-learn, Spark, etc.

Topics in Computational Social Science (TopiCSS)

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.

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.

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