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Before, he was a Senior Applied Scientist at Amazon Web Services (AWS). He led the Causal Representation Learning research team, where he pursued fundamental research in machine learning, artificial intelligence, and causality.
He received his Ph.D. in Computer Science from ETH Zurich (2020), supervised by Gunnar Rätsch (ETH Zurich) and Bernhard Schölkopf (Max Planck Institute for Intelligent Systems), where he was awarded the ETH medal for outstanding doctoral dissertation. During his Ph.D., he was supported by a Google Fellowship and was a Fellow at the Max Planck ETH Center for Learning Systems and ELLIS. During that time, he spent one year at the Max Planck Institute for Intelligent Systems and two years at Google Brain across Zurich (1.5 years as a part-time Research Consultant) and Amsterdam (6 months internship). He holds a Computer Science M.Sc. degree from ETH Zurich and a B.Sc. engineering degree (cum laude) in Information Technologies from the University of Padua (Italy).
His research on machine learning and artificial intelligence has received awards at several premier conferences and workshops, most notably the best paper award at the International Conference on Machine Learning. Francesco Locatello is heavily involved in the research community, co-organizing the first international conference on Causal Learning and Reasoning (CLeaR), ICLR and UAI workshops, and a NeurIPS competition.
He co-advises PhD students across multiple institutions:
Dingling Yao, ISTA, co-advised with Georg Martius
Francesco Montagna, University of Genoa and ELLIS, co-advised with Lorenzo Rosasco and Nicoletta Noceti
Siddhartha Gairola, MPI and ELLIS, co-advised with Bernt Schiele
Marco Fumero, La Sapienza University and ELLIS, co-advised with Emanuele Rodolà
Zhenyu Zhu, EPFL and ELLIS, co-advised with Volkan Cevher
Luca Moschella, La Sapienza University and ELLIS, co-advised with Emanuele Rodolà
Antonio Norelli, La Sapienza University and ELLIS, co-advised with Emanuele Rodolà