Prior to his visit to the Simons Institute, Martin Jaggi was a postdoctoral researcher at the École Polytechnique in Paris, France where he was working with Alexandre d'Aspremont. Jaggi earned his PhD in Theoretical Computer Science from ETH Zurich in 2011; his thesis was entitled "Sparse Convex Optimization Methods for Machine Learning." Jaggi obtained his MSc in Mathematics from ETH Zurich in 2006. He is broadly interested in methods for the analysis of large datasets, particularly at the interface between statistical machine learning, optimization and computational geometry.
- Theoretical Foundations of Big Data Analysis, Fall 2013. Research Fellow.