DATSSFLOW

Francois received his PhD in December 2018 from Stellenbosch University (SU) in South Africa where he focused on improving inference algorithms for probabilistic graphical models. Before joining the SDSC, Francois worked as a senior lecturer at the Department of Statistics and Actuarial Science at SU. His research interests include probabilistic graphical models, time series forecasting, causal inference and discovery, extreme value theory, and machine learning in general.

After finishing his Master in electrical engineering at the Ecole Fédérale de Lausanne (EPFL), Nathanaël worked as a researcher in the Acoustic Research Institute (ARI) in Vienna. In 2013, he returned to EPFL for a PhD, where he specialized in different fields of data science: signal processing, machine learning, graph theory and optimization. Furthermore, he created two open source libraries for optimization (UNLocBoX) and graph signal processing (GSPBOX). In 2017, Nathanaël Perraudin joined the Swiss Data Science Center in the ETH Zurich team as a Research Data Scientist. He focused on different aspects of deep learning in the area of generative models (VAE and GAN), recursive architectures and convolutional neural network for irregular domains. Outside office hours, he is passionate in tango dancing, tandem bike touring, skiing and rock climbing.

Michele Volpi holds a Ph.D. in Environmental Sciences from the University of Lausanne (2013). He was a postdoctoral researcher in the CALVIN group at the University of Edinburgh’s School of Informatics (2014–2016), and then a member of the Multimodal Remote Sensing and Geocomputation groups at the University of Zurich’s Department of Geography (2016–2017). He joined SDSC in 2018 as Senior Data Scientist in the Research Team and became Lead Data Scientist in 2022. Since 2025, Michele serves as Climate and Environment Domain Lead, overseeing SDSC’s activities in this area. He leads projects in geospatial machine learning, working with Earth observation and geolocated spatio-temporal data, with applications in climate and weather, ecology, natural hazards, and agriculture, among others. Michele is also a Lecturer in the Department of Environmental Systems Sciences at ETH Zurich.

Mathieu Salzmann is the Head of Engineering and the Deputy Head of Research at the Swiss Data Science Center, while also serving as a Senior Scientist and Lecturer at EPFL. He received his PhD from EPFL in 2009 and, between 2009 and 2015, has held post-doctoral and researcher positions at UC Berkeley, TTI-Chicago, and NICTA and the Australian National University. From May 2020 to February 2024, he was also a part-time Senior GNC Engineer at ClearSpace. Mathieu Salzmann has broad interests in machine learning and deep learning, with a particular focus on computer vision. He has published over 100 articles at top-tier peer-reviewed machine learning and computer vision venues and is a strong believer in collaborative work.