Alessandro Bombini's Homepage

Ufficio: FS-135, DF-256

Istituto Nazionale di Fisica Nucleare

Via Bruno Rossi, 1

Sesto Fiorentino (FI), 50019

About Me: I began my research activity during my master’s, dedicating myself to the study of theoretical aspects in black hole physics. During the three years of Ph.D. I conducted research in the context of Theoretical High Energy Physics. I continued my research moving to the University of Stockholm, where I work for three months as a project assistant.

Currently, I work as a Researcher at the INFN in the network devoted to the application of nuclear techniques to Cultural Heritage, the so-called Cultural Heritage Network (CHNet), where I am responsible for the research and development of digital infrastructure and web services for the CHNet’s Digital Heritage Laboratory (DHLab), within the EU projects European EOSC-Pillar, Ariadne+, and 4CH.

I am also the Responsible of the Digital development and ideator of the Artificial Intelligence for digital REStoration of Cultural Heritages (AIRES-CH) project, funded by a grant of Tuscany Region; AIRES-CH aims at building a web-based app for the digital restoration of pictorial artworks through Computer Vision technologies applied to nuclear imaging raw data. Two papers were already published about AIRES-CH.

I currently work as a technologist at the INFN Florence section, within the National Center 1 - ICSC National Research Center in High Performance Computing, Big Data and Quantum Computing, within the Spoke 2 “Fundamental Research”, WP2 “High Energy Physics” and WP6 “Industrial Applications & Space Economy”; I am also principal investigator for the Flaghsip 2.6.1 “Extended Computer Vision at High Rate”, where we devised distributed computing approaches for ad hoc trained deep neural network computer vision models on physics-related tasks.

I am also an Independent Expert for EU Research Executive Agency (REA) and European Innovation Council and SMEs Executive Agency (EISMEA).

Technological Research experience

05/2023 – now: Tecnologo: ML research @ ICSC; PI “Fast Extended Computer Vision”
05/2022 – 05/2023: Researcher: ML research: Responsible for the digital development and ideator of the AIRES-CH project; R&D: Lead full stack developer of the cloud-native Web services appearing in the 4CH cloud. INFN, CHNet, Firenze
09/2020 – 05/2022: Technological Researcher, Full-stack developer and Machine Learning researcher, INFN, CHNet, Firenze

Research experience: Scientific:

10/2019 – 12/2019: project assistant, Stockholms Universitet
01/2019 – 04/2019: Visiting Scientist, IPhT, CEA, Paris Saclay
10/2016 – 09/2019: Researcher at Istituto Nazionale di Fisica Nucleare (INFN), sez. Padova

Education:

2019: Ph. D. in Physics, Università di Padova
2016: M. Sc. in Theoretical Physics, 110/110 e Lode, Università di Firenze
2013: B. Sc. in Physics & Astrophysics, 110/110 e Lode, Università di Firenze

news

Jan 11, 2024	The room for the PINN lectures has changed. Updated news: 11/01: room 005 12/01: room 117 18/01: room 005 19/01: room 005 25/01: room 209 26/01: room 209 Starting time: 9:00 AM.
Nov 29, 2023	Homepage out!

selected publications

EPJc

Unitary 4-point correlators from classical geometries

Alessandro Bombini, Andrea Galliani, Stefano Giusto, and 2 more authors

Eur. Phys. J. C, 2018

Bib

@article{Bombini:2017sge,
  author = {Bombini, Alessandro and Galliani, Andrea and Giusto, Stefano and Moscato, Emanuele and Russo, Rodolfo},
  title = {{Unitary 4-point correlators from classical geometries}},
  eprint = {1710.06820},
  archiveprefix = {arXiv},
  primaryclass = {hep-th},
  doi = {10.1140/epjc/s10052-017-5492-3},
  journal = {Eur. Phys. J. C},
  volume = {78},
  number = {1},
  pages = {8},
  year = {2018},
  keywords = {article},
  dimensions = {true},
}

GARR

CHNet cloud: an EOSC-based cloud for physical technologies applied to cultural heritages

Alessandro Bombini, Lisa Castelli, Luca dell’Agnello, and 4 more authors

In Conferenza GARR 2021 - Sostenibile/Digitale. Dati e tecnologie per il futuro, 2021

Bib

@inproceedings{BombiniGarr2021,
  author = {Bombini, Alessandro and Castelli, Lisa and dell’Agnello, Luca and Felicetti, Achille and Giacomini, Francesco and Niccolucci, Franco and Taccetti, Francesco},
  title = {{CHNet cloud: an EOSC-based cloud for physical technologies applied to cultural heritages}},
  booktitle = {Conferenza GARR 2021 - Sostenibile/Digitale. Dati e tecnologie per il futuro},
  year = {2021},
  volume = {Selected Papers},
  doi = {10.26314/GARR-Conf21-proceedings-09},
  url = {https://doi.org/10.26314/GARR-Conf21-proceedings-09},
  isbn = {978-88-946629-0-0},
  publisher = {Associazione Consortium GARR},
  editor = {GARR},
  keywords = {article},
}

LNCS
The AIRES-CH Project: Artificial Intelligence for Digital REStoration of Cultural Heritages Using Nuclear Imaging and Multidimensional Adversarial Neural Networks

Alessandro Bombini, Lucio Anderlini, Luca dell’Agnello, and 3 more authors

In Image Analysis and Processing – ICIAP 2022, 2022

Abs Bib

Artificial Intelligence for digital REStoration of Cultural Heritage (AIRES-CH) aims at building a web-based app for the digital restoration of pictorial artworks through Computer Vision technologies applied to physical imaging raw data. Physical imaging techniques, such as XRF, PIXE, PIGE, and FTIR, are capable of exploring a wide range of wavelengths providing spectra that are used to infer the chemical composition of the pigments. A multidimensional neural network, specifically designed to automatically restore damaged or hidden pictorial work, will be deployed on the INFN-CHNet Cloud as a web service, freely available to authenticated researchers. In this contribution, we report the status of the project, its current results, the development plans as well as future prospects.
@inproceedings{BombiniICIAP2021, author = {Bombini, Alessandro and Anderlini, Lucio and dell'Agnello, Luca and Giacomini, Francesco and Ruberto, Chiara and Taccetti, Francesco}, editor = {Sclaroff, Stan and Distante, Cosimo and Leo, Marco and Farinella, Giovanni M. and Tombari, Federico}, title = {{The AIRES-CH Project: Artificial Intelligence for Digital REStoration of Cultural Heritages Using Nuclear Imaging and Multidimensional Adversarial Neural Networks}}, booktitle = {Image Analysis and Processing -- ICIAP 2022}, year = {2022}, publisher = {Springer International Publishing}, address = {Cham}, pages = {685--700}, isbn = {978-3-031-06427-2}, doi = {10.1007/978-3-031-06427-2_57}, url = {https://doi.org/10.1007/978-3-031-06427-2_57}, keywords = {article}, dimensions = {true}, }

LNCS

Hyperparameter Optimisation of Artificial Intelligence for Digital REStoration of Cultural Heritages (AIRES-CH) Models

Alessandro Bombini, Lucio Anderlini, Luca dell’Agnello, and 3 more authors

In Computational Science and Its Applications – ICCSA 2022 Workshops, 2022

Abs Bib

@inproceedings{BombiniICCSA2022,
  author = {Bombini, Alessandro and Anderlini, Lucio and dell'Agnello, Luca and Giacomini, Francesco and Ruberto, Chiara and Taccetti, Francesco},
  editor = {Gervasi, Osvaldo and Murgante, Beniamino and Misra, Sanjay and Rocha, Ana Maria A. C. and Garau, Chiara},
  title = {{Hyperparameter Optimisation of Artificial Intelligence for Digital REStoration of Cultural Heritages (AIRES-CH) Models}},
  booktitle = {Computational Science and Its Applications -- ICCSA 2022 Workshops},
  year = {2022},
  publisher = {Springer International Publishing},
  address = {Cham},
  pages = {91--106},
  isbn = {978-3-031-10536-4},
  doi = {10.1007/978-3-031-10536-4_7},
  url = {https://doi.org/10.1007/978-3-031-10536-4_7},
  keywords = {article},
  dimensions = {true},
}

ApplSc
A Cloud-Native Web Application for Assisted Metadata Generation and Retrieval: THESPIAN-NER

Alessandro Bombini, Ahmad Alkhansa, Laura Cappelli, and 3 more authors

Applied Sciences, 2022

Abs Bib

Within the context of the Competence Centre for the Conservation of Cultural Heritage (4CH) project, the design and deployment of a platform-as-a-service cloud infrastructure for the first European competence centre of cultural heritage (CH) has begun, and some web services have been integrated into the platform. The first integrated service is the INFN-CHNet web application for FAIR storage of scientific analysis on CH: THESPIAN-Mask. It is based on CIDOC-CRM-compatible ontology and CRMhs, describing the scientific metadata. To ease the process of metadata generation and data injection, another web service has been developed: THESPIAN-NER. It is a tool based on a deep neural network for named entity recognition (NER), enabling users to upload their Italian-written report files and obtain labelled entities. Those entities are used as keywords either to serve as (semi)automatically custom queries for the database, or to fill (part of) the metadata form as a descriptor for the file to be uploaded. The services have been made freely available in the 4CH PaaS cloud platform.
@article{app122412910, author = {Bombini, Alessandro and Alkhansa, Ahmad and Cappelli, Laura and Felicetti, Achille and Giacomini, Francesco and Costantini, Alessandro}, title = {A Cloud-Native Web Application for Assisted Metadata Generation and Retrieval: THESPIAN-NER}, journal = {Applied Sciences}, volume = {12}, year = {2022}, number = {24}, article-number = {12910}, url = {https://www.mdpi.com/2076-3417/12/24/12910}, issn = {2076-3417}, doi = {10.3390/app122412910}, keywords = {article}, dimensions = {true}, }

GARR

SUM: Save the Ukrainian Monuments - The 4CH European Competence Centre action to save Ukrainian Digital Heritage

Alessandro Bombini, Lisa Castelli, Alessandro Costantini, and 7 more authors

In Conferenza GARR 2022 - Condivisioni. La rete come strumento per costruire il futuro, 2022

Bib

@inproceedings{CastelliGarr2022,
  author = {Bombini, Alessandro and Castelli, Lisa and Costantini, Alessandro and Czelusniak, Caroline and dell’Agnello, Luca and Ronzino, Paola and Giacomini, Francesco and Niccolucci, Franco and Starodubtsev, Oleksandr and Taccetti, Francesco},
  title = {{SUM: Save the Ukrainian Monuments - The 4CH European Competence Centre action to save Ukrainian Digital Heritage}},
  booktitle = {{Conferenza GARR 2022 - Condivisioni. La rete come strumento per costruire il futuro}},
  year = {2022},
  volume = {Selected Papers},
  doi = {10.26314/GARR-Conf22-proceedings-17},
  url = {https://doi.org/10.26314/GARR-Conf22-proceedings-17},
  isbn = { 978-88-946629-1-7},
  publisher = {Associazione Consortium GARR},
  editor = {GARR},
  keywords = {article},
}

arXiv

ganX – generate artificially new XRF a python library to generate MA-XRF raw data out of RGB images

Alessandro Bombini

2023

Bib

@misc{bombini2023ganx,
  title = {ganX -- generate artificially new XRF a python library to generate MA-XRF raw data out of RGB images},
  author = {Bombini, Alessandro},
  year = {2023},
  eprint = {2304.14078},
  archiveprefix = {arXiv},
  primaryclass = {physics.app-ph},
}

GARR

A Cloud Computing infrastructure for the Competence Centre for the Conservation of Cultural Heritage

Ahmad Alkhansa, Alessandro Bombini, Alessandro Costantini, and 2 more authors

In Conferenza GARR 2023 - Saperi Interconnessi. Infrastrutture per una scienza ad alte prestazioni, 2023

Bib

@inproceedings{BombiniGarr2023,
  author = {Alkhansa, Ahmad and Bombini, Alessandro and Costantini, Alessandro and dell’Agnello, Luca and Taccetti, Francesco},
  title = {{A Cloud Computing infrastructure for the Competence Centre for the Conservation of Cultural Heritage}},
  booktitle = {{Conferenza GARR 2023 - Saperi Interconnessi. Infrastrutture per una scienza ad alte prestazioni}},
  year = {2023},
  volume = {Selected Papers},
  doi = {10.26314/GARR-Conf23-proceedings_07},
  url = {https://doi.org/10.26314/GARR-Conf23-proceedings_07},
  isbn = { 978-88-946629-2-4},
  publisher = {Associazione Consortium GARR},
  editor = {GARR},
  keywords = {article},
}

MLST

Datacube segmentation via Deep Spectral Clustering

Bombini, Alessandro and Bofías, Fernando García-Avello and Bracci, Caterina and Ginolfi, Michele and Ruberto, Chiara

Machine Learning: Science and Technology, 2024

Bib

@article{bombini2024datacube,
  author = {{Bombini, Alessandro and Bofías, Fernando García-Avello and Bracci, Caterina and Ginolfi, Michele and Ruberto, Chiara}},
  title = {{Datacube segmentation via Deep Spectral Clustering}},
  journal = {Machine Learning: Science and Technology},
  url = {http://iopscience.iop.org/article/10.1088/2632-2153/ad622f},
  year = {2024},
}