Meet the GMLG staff

Cesare Alippi

Professor with Università della Svizzera italiana and Politecnico di Milano
IEEE Fellow - ELLIS Fellow

His research focuses on graph-based learning, learning in non-stationary environments, lifelong learning, intelligence in embedded, cyber-physical systems and the Internet-of-Things.


Slobodan Lukovic

Post-doc Researcher

His work is focused on the energy efficiency and reliability of Smart Grids.

Daniele Zambon

Post-doc Researcher

His research focuses on learning in non-stationary environments with spatiotemporal and graph data.

Andrea Cini

Ph.D. Student

He is interested in relational inductive biases for the processing of spatiotemporal data.

Ivan Marisca

Ph.D. Student

His studies concern the analysis and prediction of irregular spatiotemporal data.

Luca Butera

Ph.D. Student

Working on object detection and computer vision.

Alessandro Manenti

Ph.D. Student

He studies spatiotemporal data processing using graph latent spaces.

Tommaso Marzi

Ph.D. Student

His research focuses on graph-based prediction and control in reinforcement learning.

Stefano Imoscopi

Research Collaborator

He works on applied research projects. His focus is on time series forecasting for the energy industry.

Federico Bombardieri

Research Collaborator

His research focuses on machine learning for hydrology.


Lorenzo Livi

Assistant professor at the University of Manitoba, Winnipeg (Canada)

His research interests lie at the intersection of machine learning and complex dynamical systems, with particular emphasis on graph-based methods.

Filippo Maria Bianchi

Associate professor at the Arctic University of Norway, Tromsø (Norway)

His research covers deep learning in recurrent neural networks, graph neural networks, time series analysis, and reservoir computing.


  • Pietro Verzelli, Post-doc Researcher at Johannes Gutenberg University Mainz.
    Ph.D., relationships between dynamical systems and machine learning. (2017-2022)
  • Daniele Grattarola, Research Scientist at Isomorphic Labs.
    Ph.D., graph neural networks for dynamical systems and computational biology. (2017-2021)
  • Alberto Gasparin, Applied Scientist at Amazon Research (Berlin).
    Politecnico di Milano, Milan (Italy), deep learning prediction and smart grids. (2017-2021)
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