On this page you can find more detail about my work, including my interests, publications, conferences, and talks. Also, you may be interested in my University Webpage, here.

Curriculum Vitae CV:

My research is focused on Quantum Computation and Information, and I’m interested also in topics coming from Theoretical Computer Science. I’m half a Theoretician and Programmer (I love spending time on my computer), using both approaches when dealing with a problem.

At the moment, for my PhD I am investigating and studying one of the most interesting application of Quantum Computing, that is Quantum Machine Learning.

Programming languages and tools: Qiskit, Pennylane, Python, Fortran, Mathematica, …

Publications

[Last updated: 12/06/22] For an always up-to-date list, please check Google Scholar , arXiv, Orcid .

• Ballarin M., Mangini S., Montangero S., Macchiavello C. and Mengoni R. (2022). Entanglement entropy production in Quantum Neural Networks, arXiv preprint arXiv:2206.02474.

• Scala F., Mangini S., Macchiavello C., Gerace D., Bajoni D. and Gerace D. (2022). Quantum variational learning for entanglement witnessing, arXiv preprint arXiv:2205.10429.

• Mangini S., Marruzzo A., Piantanida M., Gerace D., Bajoni D. and Macchiavello C. (2022). Quantum neural network autoencoder and classifier applied to an industrial case study, arXiv preprint arXiv:2205.04127.

• Di Sipio R., Huang J. H., Chen S. Y. C., Mangini S. and Worring M. (2022). The Dawn of Quantum Natural Language Processing, ICASSP 2022 - IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022, pp. 8612-8616.

• Mangini S., Maccone L., Macchiavello C. (2021). Qubit noise deconvolution, arXiv preprint arXiv:2112.03043.

• Mangini S., Tacchino F., Gerace D., Bajoni D. and Macchiavello C. (2021). Quantum computing models for artificial neural networks, EPL (Europhysics Letters) 134(1), 10002.

• Tacchino F., Mangini S., Barkoutsos P. K., Macchiavello C., Gerace D., Tavernelli I. and Bajoni D. (2021). Variational learning for artificial neural networks, IEEE Transactions on Quantum Engineering, vol. 2, pp. 1-10.

• Mangini S., Tacchino F., Macchiavello C., Gerace D. and Bajoni D. (2020). Quantum computing model of an artificial neuron with continuously valued input data, Machine Learning: Science and Technology 1(4), 045008.

• Benatti F., Mancini S. and Mangini S. (2020). Continuous variable quantum perceptron, International Journal of Quantum Information 17(08), 1941009.

Talks

• Summer School: Machine Learning for Quantum Physics and Chemistry (University of Warsaw), 2021.
  Contributed talk: “Variational Learning for Quantum Artificial Neural Networks” (Slides; Video; Paper).
• Young Italian Quantum Information Science (YIQIS), 2020.
  Invited speaker: “Quantum Computing models for artificial neurons” (Slides).

Coding and Hackathons Conferences

• Qiskit Hackathon Euorpe: Research Study Group (2021), organized by IBM.
  Project: Quantum Reinforcement Learning with Qiskit (code on GitHub).
• Quantum Open Source Foundation (QOSF) Mentorship Program, Mentee (2020).
  Project: Learning to Learn with Quantum Artificial Neural Networks, featured as a Demo on PennyLane’s website.
• Hackathon on CEREBELLUM MODELLING (2020), organized by Human Brain Project (HBP).
  Link to event description