Bilde av Bianchi, Filippo Maria
Bilde av Bianchi, Filippo Maria
Associate Professor Department of Mathematics and Statistics filippo.m.bianchi@uit.no +4777625176 Tromsø You can find me here

Filippo Maria Bianchi


Job description

My research interests lie at the intersection between machine learning, dynamical systems, and complex networks. The main areas where I apply my research are energy analytics and remote sensing.

More info at:


  • Karoline Ingebrigtsen, Filippo Maria Bianchi, Sigurd Bakkejord, Inga Setså Holmstrand, Matteo Chiesa :
    Identifying conditions leading to power quality events in Arctic Norway: Feature selection
    Applied Energy 2024 DOI
  • Ivan Marisca, Cesare Alippi, Filippo Maria Bianchi :
    Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling
    Proceedings of Machine Learning Research (PMLR) 2024 FULLTEKST / ARKIV / DOI
  • Michele Guerra, Simone Scardapane, Filippo Maria Bianchi :
    Probabilistic Load Forecasting With Reservoir Computing
    IEEE Access 15. December 2023 ARKIV / DOI
  • Filippo Maria Bianchi, Veronica Lachi :
    The expressive power of pooling in Graph Neural Networks
    Advances in Neural Information Processing Systems 2023 ARKIV / FULLTEKST / DOI
  • Michele Guerra, Indro Spinelli, Simone Scardapane, Filippo Maria Bianchi :
    Explainability in subgraphs-enhanced Graph Neural Networks
    Proceedings of the Northern Lights Deep Learning Workshop 23. January 2023 ARKIV / DOI
  • Jonas Berg Hansen, Filippo Maria Bianchi :
    Total Variation Graph Neural Networks
    Proceedings of Machine Learning Research (PMLR) 2023 ARKIV / SAMMENDRAG
  • Filippo Maria Bianchi :
    Simplifying Clustering with Graph Neural Networks
    Proceedings of the Northern Lights Deep Learning Workshop 23. January 2023 FULLTEKST / ARKIV / DOI
  • Andrea Cini, Ivan Marisca, Filippo Maria Bianchi, Cesare Alippi :
    Scalable Spatiotemporal Graph Neural Networks
    Proceedings of the AAAI Conference on Artificial Intelligence 2023 FULLTEKST / ARKIV / DOI
  • Odin Foldvik Eikeland, Colin C. Kelsall, Kyle Buznitsky, Shomik Verma, Filippo Maria Bianchi, Matteo Chiesa et al.:
    Power availability of PV plus thermal batteries in real-world electric power grids
    Applied Energy 2023 ARKIV / DOI
  • Odin Foldvik Eikeland, Filippo Maria Bianchi, Inga Setså Holmstrand, Sigurd Bakkejord, Sergio Santos Hernandez, Matteo Chiesa :
    Uncovering Contributing Factors to Interruptions in the Power Grid: An Arctic Case
    Energies 03. January 2022 ARKIV / DOI
  • Odin Foldvik Eikeland, Finn Dag Hovem, Tom Eirik Olsen, Matteo Chiesa, Filippo Maria Bianchi :
    Probabilistic forecasts of wind power generation in regions with complex topography using deep learning methods: An Arctic case
    Energy Conversion and Management: X 2022 ARKIV / DOI
  • Jonas Berg Hansen, Stian Normann Anfinsen, Filippo Maria Bianchi :
    Power Flow Balancing With Decentralized Graph Neural Networks
    IEEE Transactions on Power Systems 01. August 2022 ARKIV / DOI
  • Iver Martinsen, Alf Harbitz, Filippo Maria Bianchi :
    Age prediction by deep learning applied to Greenland halibut (Reinhardtius hippoglossoides) otolith images
    PLOS ONE 2022 ARKIV / DOI
  • Daniele Grattarola, Daniele Zambon, Filippo Maria Bianchi, Cesare Alippi :
    Understanding Pooling in Graph Neural Networks
    IEEE Transactions on Neural Networks and Learning Systems 21. July 2022 ARKIV / DOI
  • Jakob Grahn, Filippo Maria Bianchi :
    Recognition of Polar Lows in Sentinel-1 SAR Images With Deep Learning
    IEEE Transactions on Geoscience and Remote Sensing 06. September 2022 ARKIV / DOI
  • Vilde Jensen, Filippo Maria Bianchi, Stian Normann Anfinsen :
    Ensemble Conformalized Quantile Regression for Probabilistic Time Series Forecasting
    IEEE Transactions on Neural Networks and Learning Systems 2022 ARKIV / DOI
  • Luigi Tommaso Luppino, Mads Adrian Hansen, Michael Kampffmeyer, Filippo Maria Bianchi, Gabriele Moser, Robert Jenssen et al.:
    Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images
    IEEE Transactions on Neural Networks and Learning Systems 12. May 2022 DOI
  • Anne Gerd Imenes, Nadia Saad Noori, Ole Andreas Nesvåg Uthaug, Robert Kröni, Filippo Maria Bianchi, Nabil Belbachir :
    A Deep Learning Approach for Automated Fault Detection on Solar Modules Using Image Composites
    IEEE conference proceedings 2021 FULLTEKST / DOI
  • Huamin Ren, Filippo Maria Bianchi, Jingyue Li, Rasmus L. Olsen, Robert Jenssen, Stian Normann Anfinsen :
    Towards Applicability: A Comparative Study on Non-Intrusive Load Monitoring Algorithms
    IEEE conference proceedings 2021 DOI
  • Filippo Maria Bianchi, Claudio Gallicchio, Alessio Micheli :
    Pyramidal Reservoir Graph Neural Network
    Neurocomputing 2021 DOI
  • Odin Foldvik Eikeland, Inga Setså Holmstrand, Sigurd Bakkejord, Matteo Chiesa, Filippo Maria Bianchi :
    Detecting and Interpreting Faults in Vulnerable Power Grids With Machine Learning
    IEEE Access 2021 ARKIV / DOI
  • Filippo Maria Bianchi, Daniele Grattarola, Lorenzo Livi, Cesare Alippi :
    Graph Neural Networks With Convolutional ARMA Filters
    IEEE Transactions on Pattern Analysis and Machine Intelligence 26. January 2021 DOI
  • Karl Øyvind Mikalsen, Cristina Soguero Ruiz, Filippo Maria Bianchi, Arthur Revhaug, Robert Jenssen :
    Time series cluster kernels to exploit informative missingness and incomplete label information
    Pattern Recognition 2021 ARKIV / DOI
  • Luigi Tommaso Luppino, Michael Kampffmeyer, Filippo Maria Bianchi, Gabriele Moser, Sebastiano Bruno Serpico, Robert Jenssen et al.:
    Deep Image Translation With an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection
    IEEE Transactions on Geoscience and Remote Sensing 2021 ARKIV / DOI
  • Odin Foldvik Eikeland, Filippo Maria Bianchi, Matteo Chiesa, Harry Apostoleris, Morten Hansen, Yu-Cheng Chiou :
    Predicting Energy Demand in Semi-Remote Arctic Locations
    Energies 2021 ARKIV / DOI
  • Filippo Maria Bianchi, Simone Scardapane, Sigurd Løkse, Robert Jenssen :
    Reservoir Computing Approaches for Representation and Classification of Multivariate Time Series
    IEEE Transactions on Neural Networks and Learning Systems 2021 ARKIV / DOI
  • Martin Wibe Rypdal, Kristoffer Rypdal, Ola Løvsletten, Sigrunn Holbek Sørbye, Elinor Ytterstad, Filippo Maria Bianchi :
    Estimation of Excess Mortality and Years of Life Lost to COVID-19 in Norway and Sweden between March and November 2020
    International Journal of Environmental Research and Public Health (IJERPH) 2021 ARKIV / DOI
  • Filippo Maria Bianchi, Daniele Grattarola, Cesare Alippi :
    Spectral Clustering with Graph Neural Networks for Graph Pooling
    Proceedings of Machine Learning Research (PMLR) 2020
  • Filippo Maria Bianchi, Martine Espeseth, Njål Trygve Borch :
    Large-Scale Detection and Categorization of Oil Spills from SAR Images with Deep Learning
    Remote Sensing 2020 ARKIV / DOI
  • Changkyu Choi, Filippo Maria Bianchi, Michael Kampffmeyer, Robert Jenssen :
    Short-Term Load Forecasting with Missing Data using Dilated Recurrent Attention Networks
    Proceedings of the Northern Lights Deep Learning Workshop 2020 ARKIV / DOI
  • Filippo Maria Bianchi, Jakob Grahn, Markus Eckerstorfer, Eirik Malnes, Hannah Vickers :
    Snow avalanche segmentation in SAR images with Fully Convolutional Neural Networks
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2020 DOI
  • Kristoffer Rypdal, Filippo Maria Bianchi, Martin Rypdal :
    Intervention Fatigue is the Primary Cause of Strong Secondary Waves in the COVID-19 Pandemic
    International Journal of Environmental Research and Public Health (IJERPH) 2020 DOI
  • Filippo Maria Bianchi, Daniele Grattarola, Lorenzo Livi, Cesare Alippi :
    Hierarchical Representation Learning in Graph Neural Networks With Node Decimation Pooling
    IEEE Transactions on Neural Networks and Learning Systems 2020 ARKIV / DOI
  • Michael C. Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Lorenzo Livi, Arnt Børre Salberg, Robert Jenssen :
    Deep divergence-based approach to clustering
    Neural Networks 2019 ARKIV / DOI
  • Karl Øyvind Mikalsen, Cristina Soguero-Ruiz, Filippo Maria Bianchi, Robert Jenssen :
    Noisy multi-label semi-supervised dimensionality reduction
    Pattern Recognition 2019 ARKIV / DOI
  • Luigi Tommaso Luppino, Filippo Maria Bianchi, Gabriele Moser, Stian Normann Anfinsen :
    Unsupervised Image Regression for Heterogeneous Change Detection
    IEEE Transactions on Geoscience and Remote Sensing 14. August 2019 ARKIV / FULLTEKST / DOI
  • Filippo Maria Bianchi, Lorenzo Livi, Karl Øyvind Mikalsen, Michael C. Kampffmeyer, Robert Jenssen :
    Learning representations of multivariate time series with missing data
    Pattern Recognition 2019 ARKIV / DOI
  • Alessandro Cinti, Filippo Maria Bianchi, Alessio Martino, Antonello Rizzi :
    A Novel Algorithm for Online Inexact String Matching and its FPGA Implementation
    Cognitive Computation 2019 ARKIV / DOI
  • Ralph Kube, Filippo Maria Bianchi, Dan Brunner, Brian LaBombard :
    Outlier classification using autoencoders: Application for fluctuation driven flows in fusion plasmas
    Review of Scientific Instruments 2019 ARKIV / DOI
  • Filippo Maria Bianchi :
    Learning representations of multivariate time series with missing data
    Pattern Recognition 2019 DOI
  • Davide Bacciu, Filippo Maria Bianchi, Benjamin Paassen, Cesare Alippi :
    Deep learning for graphs
    2018
  • Michael C. Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Robert Jenssen, Lorenzo Livi :
    The deep kernelized autoencoder
    Applied Soft Computing 2018 ARKIV / DOI
  • Filippo Maria Bianchi, Karl Øyvind Mikalsen, Robert Jenssen :
    Learning compressed representations of blood samples time series with missing data
    2018 DOI
  • Luigi Tommaso Luppino, Filippo Maria Bianchi, Gabriele Moser, Stian Normann Anfinsen :
    Remote sensing image regression for heterogeneous change detection
    IEEE Signal Processing Society 2018 FULLTEKST / ARKIV / DOI
  • Benjamin Ricaud, Filippo Maria Bianchi :
    Learning on Graphs (LoG) meetup in Tromsø
    2023
  • Benjamin Ricaud, Volodymyr Miz, Filippo Maria Bianchi, Nicolas Aspert :
    Introduction to Graph Machine Learning
    2022 DATA
  • Anne Gerd Imenes, Nadia Saad Noori, Ole Andreas Nesvåg Uthaug, Robert Kröni, Filippo Maria Bianchi, Nabil Belbachir :
    A Deep Learning Approach for Automated Fault Detection on Solar Modules Using Image Composites
    2021 FULLTEKST
  • Nadia Saad Noori, Tor Inge Waag, Filippo Maria Bianchi :
    Condition Monitoring System for Internal Blowout Prevention (IBOP) in Top Drive Assembly System using Discrete Event Systems and Deep Learning Approaches
    2020 ARKIV
  • Changkyu Choi, Filippo Maria Bianchi, Michael Kampffmeyer, Robert Jenssen :
    Short-Term Load Forecasting with Missing Data using Dilated Recurrent Attention Networks
  • Filippo Maria Bianchi, Ponnuthurai Nagaratnam Suganthan :
    Non-iterative Learning Approaches and Their Applications
    Cognitive Computation 2020 ARKIV / DOI

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    Research interests

    Machine learning; Graph theory; Time series analysis


    Member of research group