Martin Jaggi

martin.jaggi@epfl.ch http://mlo.epfl.ch

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EPFL IC IINFCOM MLO
INJ 341 (Bâtiment INJ)
Station 14
1015 Lausanne

+41 21 693 70 59
Office: INJ 341
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+41 21 693 70 59
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Expertise

Machine Learning, Optimization

Group Webpage:

mlo.epfl.ch

Biography Awards Teaching & PhD

Martin Jaggi is an Associate Professor at EPFL, heading the Machine Learning and Optimization Laboratory. Before that, he was a post-doctoral researcher at ETH Zurich, at the Simons Institute in Berkeley, and at école Polytechnique in Paris. He has earned his PhD in Machine Learning and Optimization from ETH Zurich in 2011, and a MSc in Mathematics also from ETH Zurich.

Awards

2021 Credit Suisse Award for Best Teaching

2021

Google Faculty Research Award

2017

Teaching & PhD

Courses

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.

Optimization for machine learning

CS-439

This course teaches an overview of modern optimization methods, for applications in machine learning and data science. In particular, scalability of algorithms to large datasets will be discussed in theory and in implementation.

Topics in Machine Learning Systems

CS-723

This course will cover the latest technologies, platforms and research contributions in the area of machine learning systems. The students will read, review and present papers from recent venues across the systems for ML spectrum.