The people of GMLG
His work is focused on the energy efficiency and reliability of Smart Grids.
His research focuses on learning in non-stationary environments with spatiotemporal and graph data.
He is interested in relational inductive biases for the processing of spatiotemporal data.
His studies concern the analysis and prediction of irregular spatiotemporal data.
He studies spatiotemporal data processing using graph latent spaces.
His research focuses on graph-based prediction and control in reinforcement learning.
He works on applied research projects. His focus is on time series forecasting for the energy industry.
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.
- 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)