Roberto Neglia

Me in Tenerife in 2024

I’m a Ph.D. fellow at the Department of Mathematics and Statistics at UiT The Arctic University of Norway, where I’m part of the Northernmost Graph Machine Learning Group. I work under the superivision of Filippo Maria Bianchi on basic research in machine learning for graphs and time series data, with a focus on scalable spatiotemporal models and uncertainty quantification.

Before that, I completed a Master’s degree in High Performance Computing Engineering at Politecnico di Milano and in Computational Science at Università della Svizzera italiana, in the framework of the prestigious EUMaster4HPC double degree program.

news

Oct 07, 2025	I’m excited to share that a new preprint titled “ResCP: Residual Conformal Prediction for Time Series Forecasting” is now available on arXiv! We propose ResCP, a novel conformal prediction method for time series forecasting. ResCP leverages the efficiency and representation capabilities of Reservoir Computing to dynamically reweight conformity scores at each time step. This allows us to account for local temporal dynamics when modeling the error distribution without compromising computational scalability. Moreover, we prove that, under reasonable assumptions, ResCP achieves asymptotic conditional coverage.

Oct 07, 2025

I’m excited to share that a new preprint titled “ResCP: Residual Conformal Prediction for Time Series Forecasting” is now available on arXiv!

We propose ResCP, a novel conformal prediction method for time series forecasting. ResCP leverages the efficiency and representation capabilities of Reservoir Computing to dynamically reweight conformity scores at each time step. This allows us to account for local temporal dynamics when modeling the error distribution without compromising computational scalability. Moreover, we prove that, under reasonable assumptions, ResCP achieves asymptotic conditional coverage.