resume

Theoretical physicist turned computer scientist. Senior Researcher at LINKS Foundation, working on High-Performance Computing, Quantum–HPC integration and Machine Learning at scale.

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Main interests

• High-Performance Computing
• Quantum–HPC integration
• Machine Learning at scale

Education

PhD, Computer Science — University of Torino · Torino, Italy · 2015 – 2019

• Thesis: Deep Learning at Scale with Nearest Neighbours Communications.
• Supervisor: Marco Aldinucci. Funded by Noesis Solutions.

MSc, Theoretical Physics — University of Torino · Torino, Italy · 2015 · 104/110

• Collegio Universitario “R. Einaudi”, Torino.
• Scholarship “Piano Lauree Scientifiche 2008”, Società Italiana di Fisica.

Experience

Senior Researcher, Advanced Computing — LINKS Foundation · Torino, Italy · 2021 – present

• Co-coordinator of CLEAR-EO (Horizon Europe) and WP3 lead; proposals for Horizon Europe, EuroHPC and national projects.
• Lagrange — operations lead of Italy’s first publicly-accessible quantum computer (IQM Spark), open-source management stack; first hybrid HPC–QC job fully run in Italy, with Leonardo.
• Quantum–HPC integration — hybrid scheduling (Slurm, QPU sharing); co-lead of EQS3 working groups.
• Quantum algorithms — QUBO/MIS on neutral atoms and annealers; QEC4QEA deputy WP3 lead.
• Infrastructure — internal services (GitLab, Nextcloud, JupyterHub), scaled from group to institute-wide.

Research Engineer — Noesis Solutions · Novara, Italy · 2015 – 2021

• ML methodologies for engineering; numerical code and software stack.
• Source code management redesign; technical contact for funded projects.

Funded research projects

See projects for the full list and details.

Skills

• Parallel & GPU computing: MPI/OpenMP, CUDA, BLAS/LAPACK
• HPC & Cloud infrastructure: SLURM, Docker, OpenStack, Juju, GitLab CI/CD, Linux, IP networking (CISCO CCNA course, 2008)
• Machine Learning: Keras, PyTorch, Dask
• Quantum computing: Qiskit, Quantum–HPC integration, neutral-atom optimization, quantum annealing
• Programming: C++, Python, CUDA, Fortran, Git
• Research project management: proposal writing, presentations, communication of results, formalization of requirements, decomposition of problems, LaTeX

Languages

• Italian: Native speaker
• English: Fluent (C1 — General English Super Intensive, Alpha College of English, Dublin, 2012)
• French: Basic

Academic activity

Selected publications

See publications for the full list.

1. Cipollini, M. et al. Three ways to share a QPU: Scheduling strategies for hybrid Quantum-HPC applications. Future Generation Computer Systems 185, 108699 (2026).
2. Viviani, P. et al. Lagrange: Operating Italy’s First Publicly-Accessible Quantum Computer for Research and Education. arXiv:2604.21695 (2026).
3. Rocco, R. et al. Dynamic Solutions for Hybrid Quantum-HPC Resource Allocation in 2025 IEEE International Conference on Quantum Computing and Engineering (QCE) (2025).
4. Viviani, P. et al. Assessing the Elephant in the Room in Scheduling for Current Hybrid HPC-QC Clusters in 2025 IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W) (2025).
5. Vercellino, C. et al. A Machine Learning Approach for an HPC Use Case: the Jobs Queuing Time Prediction. Future Generation Computer Systems 143, 215–230 (2023).
6. Vercellino, C. et al. BBQ-mIS: A Parallel Quantum Algorithm for Graph Coloring Problems in 2023 IEEE International Conference on Quantum Computing and Engineering (QCE) (2023).
7. Viviani, P. et al. Deep Learning for Real-Time Neural Decoding of Grasp in Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track (Springer, 2023), 379–393.
8. Savio, P. et al. Accelerating Legacy Applications with Spatial Computing Devices. The Journal of Supercomputing (2022).
9. Scionti, A. et al. Distributed HPC Resources Orchestration for Supporting Large-Scale Workflow Execution in HPC, Big Data, and AI Convergence Towards Exascale (CRC Press, 2022).
10. Vercellino, C. et al. Neural-Powered Unit Disk Graph Embedding: Qubits Connectivity for Some QUBO Problems in 2022 IEEE International Conference on Quantum Computing and Engineering (QCE) (2022), 186–196.
11. Viviani, P., Drocco, M., Baccega, D., Colonnelli, I. & Aldinucci, M. Deep Learning at Scale in Proc. of 27th Euromicro PDP (IEEE, Pavia, 2019), 124–131.
12. Aldinucci, M. et al. HPC4AI, an AI-on-demand federated platform endeavour in ACM Computing Frontiers (Ischia, 2018).
13. Viviani, P., Torquati, M., Aldinucci, M. & d’Ippolito, R. Multiple back-end support for the Armadillo linear algebra interface in Proc. of the 32nd ACM Symposium on Applied Computing (SAC) (Marrakesh, 2017), 1566–1573.

Other

• Teaching for the Master in Quantum Computing and Communication (Politecnico di Torino).
• Co-supervisor of 6 M.Sc. theses.
• Program Committee member, Euromicro International Conference on Parallel, Distributed, and Network-based Processing (PDP) for 2018 (also session chair), 2019 and 2020.
• Program Committee member, Artifact Evaluation, Euro-Par 2018.
• Program Committee member, 16th IEEE International Conference on Scalable Computing and Communications (ScalCom 2016).

Free time

• Avid traveller and photographer — see the portfolio. Expedition photographer for the OASIS archaeological project (Kharga, Egypt, 2013 — funded by Fondazione Collegio delle Università Milanesi and the American University in Cairo) and for Collegio Universitario “R. Einaudi” (Torino, 2012–2014).
• Former track & field athlete — javelin throw, regional and national competitions (1997–2012); now turned to fatherhood.
• PADI Advanced Open Water Diver (since 2004).
• Exchange student at Tauranga Boys’ College, New Zealand (2006); volunteer at the IAAF Athletics World Championship (Berlin, 2009).