Giacomo Vitali

Dottorando in Ingegneria Informatica E Dei Sistemi , 38o ciclo (2022-2025)
Dipartimento di Automatica e Informatica (DAUIN)

Docente esterno e/o collaboratore didattico
Dipartimento di Automatica e Informatica (DAUIN)

Profilo

Dottorato di ricerca

Argomento di ricerca

Quantum Machine Learning Applications and Algorithms for Technology Transfer

Tutori

Presentazione della ricerca

Poster

Interessi di ricerca

Parallel and distributed systems, Quantum computing

Biografia

Giacomo Vitali graduated in Physics of Fundamental Interactions at University of Pisa in 2018 with a Thesis titled "Development of a Fast Simulation for the LHCb Calorimeter". After a year as assistant researcher at the Normale di Pisa, he moved to Fondazione LINKS as senior researcher in computer science for the Advanced Computing, Photonics and Electromagnetics (CPE) domain, dealing with HPC-related topics, like optimization and Quantum Computing. During this experience, he started working as main responsible of a small group of researchers on Quantum Computing topics, in particular on the development of hybrid algorithms for solving complex problems of various types (Quantum Machine Learning, Combinatorial Optimization, Material Simulation, Quantum Chemistry) related to industrial applications. He worked with several architectures, especially Quantum Annealers and Neutral Atoms platform, developing skills in Quantum Programming with specific tools.
In 2022, he started a PhD course at the Politecnico di Torino at the Department of Control And Computer Engineering (DAUIN) under the supervision of Prof. Bartolomeo Montrucchio of the GRAINS group on "Quantum Machine Learning Applications and Algorithms for Technology Transfer".
Given the embryonic stage and the limitations of the NISQ-era Quantum Computing platforms in terms of coherence time, qubit connectivity, etc. a clear Quantum Computing advantage over classical architectures is still to be demonstrated. Hence, the main the objective of the PhD research work is to enable Quantum Machine Learning techniques for industrial and scientific applications, and asses the technology readiness. To this end, it is required to:
  • Analyze and identify appropriate use-cases and the most promising QML algorithms
  • Optimize, implement and run the hybrid workflows on classical resources and available real quantum devices
  • Benchmark the results against state-of-the-art classical Machine Learning methods.

Didattica

Insegnamenti

Corso di laurea magistrale

Corso di laurea di 1° livello

  • Informatica. A.A. 2024/25, INGEGNERIA AEROSPAZIALE. Collaboratore del corso
  • Informatica. A.A. 2023/24, INGEGNERIA INFORMATICA. Collaboratore del corso
MostraNascondi A.A. passati

Ricerca

Gruppi di ricerca

Pubblicazioni

Pubblicazioni più recenti Vedi tutte le pubblicazioni su Porto@Iris

  • Giusto, Edoardo; Iurlaro, Gabriele; Montrucchio, Bartolomeo; Scionti, Alberto; Terzo, ... (2024)
    Harnessing a 256-qubit Neutral Atom Simulator for Graph Classification. In: 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), Montreal (CA), September 15–20, 2024, pp. 296-305. ISBN: 979-8-3315-4137-8
    Contributo in Atti di Convegno (Proceeding)
  • Vercellino, Chiara; Vitali, Giacomo; Viviani, Paolo; Scionti, Alberto; Terzo, Olivier; ... (2024)
    Harnessing DEN models for quantum computing tasks on neutral atom QPUs. In: 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), Montreal (CA), September 15–20, 2024, pp. 217-222. ISBN: 979-8-3315-4137-8
    Contributo in Atti di Convegno (Proceeding)
  • Lubrano, Francesco; Vercellino, Chiara; Vitali, Giacomo; Viviani, Paolo; Scionti, ... (2024)
    Advanced Resource Allocation in the Context of Heterogeneous Workflows Management. In: WiDE '24: 2nd Workshop on Workflows in Distributed Environments, Athens (GR), 22 April 2024, pp. 14-20. ISBN: 979-8-4007-0546-5
    Contributo in Atti di Convegno (Proceeding)
  • Vercellino, Chiara; Vitali, Giacomo; Viviani, Paolo; Giusto, Edoardo; Scionti, Alberto; ... (2023)
    BBQ-mIS: a parallel quantum algorithm for graph coloring problems. In: 2023 IEEE International Conference on Quantum Computing and Engineering (QCE), Bellevue, WA (USA), September 17–22, 2023, pp. 141-147. ISBN: 979-8-3503-4323-6
    Contributo in Atti di Convegno (Proceeding)
  • Viviani, Paolo; Gesmundo, Ilaria; Ghinato, Elios; Agudelo-Toro, Andres; Vercellino, ... (2023)
    Deep Learning for Real-Time Neural Decoding of Grasp. In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in DatabasesT (ECML PKDD 2023), Turin (Italy), September 18–22, 2023, pp. 379-393. ISSN 0302-9743. ISBN: 978-3-031-43426-6
    Contributo in Atti di Convegno (Proceeding)