Martin Jaggi

Expertise Machine Learning, Optimization Group Webpage: mlo.epfl.ch 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. Teaching & PhD PhD Students El Mahdi Chayti, Dongyang Fan, Alexander Hägele, Simla Burcu Harma, Bettina Ursula Messmer, Diba Hashemi, Matteo Pagliardini, Vinko Sabolcec, Simin Fan, Alejandro Hernández Cano Past EPFL PhD Students Prakhar Gupta, Sai Praneeth Reddy Karimireddy, Tao Lin, Jean-Baptiste Cordonnier, Thijs Vogels, Lie He, Anastasiia Koloskova, Mohtashami Amirkeivan, Atli Kosson Past EPFL PhD Students as codirector Mario Paulo Drumond Lages De Oliveira, Vinitra Swamy Courses 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 studentswill read, review and present papers from recent venues across the systems for ML spectrum. Awards 2021 Credit Suisse Award for Best Teaching 2021 Google Faculty Research Award 2017