Daniele Zambon

I am a post-doc at the Swiss AI Lab IDSIA and USI (CH) in the graph machine learning group.

The focus of my research is graph representation learning, learning in non-stationary environments, and graph stream processing.

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About me

I obtained my Ph.D. from USI Università della Svizzera italiana (CH) under the supervision of Prof. Cesare Alippi (from USI and POLIMI) and Prof. Lorenzo Livi (from Univ. of Manitoba, CA, and Univ. of Exeter, UK). My research dealt with statistical tests for anomaly and change detection in sequences of graphs, graph representation learning, and learning in non-stationary environments. You can find a list of my publications here.

I have been visiting researcher at the University of Florida (US) working on kernel adaptive methods and at the University of Exeter (UK) exploring embeddings onto Riemannian manifolds. I have also been an intern at STMicroelectronics (Italy) where I developed my Master’s thesis on sparse models for anomaly detection. I received Master’s and Bachelor’s degrees from the Università degli Studi di Milano (Italy) focusing on approximation theory and mathematical statistics.

I am (or have been) in the program committee of top-tier conferences and journals of the field, including IEEE TNNLS, IEEE TSP, IEEE PAMI, IEEE IJCNN, NeurIPS, ICLR, ICML, CVPR.







I regularly serve as a teacher in Master’s and Bachelor’s degree programs at USI holding lectures, lab sessions, and examinations.