Daniele Zambon is a post-doc at the Swiss AI Lab IDSIA / USI-SUPSI working on graph representation learning, learning in non-stationary environments, and graph stream processing.
Daniele obtained his Ph.D. from USI 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). Daniele has been visiting researcher at the University of Florida (US) working on kernel adaptive methods and the University of Exeter (UK) exploring embeddings onto Riemannian manifolds. I have also been an intern at STMicroelectronics (Italy) where he developed his 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.