74960 citations, h-index 118 (updated 02/2025) according to the SCOPUS page about me. Full list of publications available via my ORCID ID. You can also check my Google Scholar page.

Latest preprints

• Z. Zaher et al. (P.V.), “Optimization of a cosmic muon tomography scanner for cargo border control inspection”, submitted to Journal of Applied Physics, (2507.10253)
• C. A. Argüelles et al. (P.V.), “TAMBO: A Deep-Valley Neutrino Observatory”, submitted to Nature Astronomy, (2507.08070)
• S. Caron et al. (P.V.), “Strategic White Paper on AI Infrastructure for Particle, Nuclear, and Astroparticle Physics: Insights from JENA and EuCAIF”, (2503.14192)
• K. G. Barman et al. (P.V.), “Large Physics Models: Towards a collaborative approach with Large Language Models and Foundation Models”, submitted to Nature physics roadmap, 2501.05382

Latest publication highlights

• M. Pereira Martínez, X. Cid Vidal, Pietro Vischia, “Automatic Optimization of a Parallel-Plate Avalanche Counter with Optical Readout”, Particles 2025, 8(1), 26 (10.3390/particles8010026, 2503.02538) -M. Aehle et al. (P.V.), “Progress in End-to-End Optimization of Detectors for Fundamental Physics with Differentiable Programming “, Reviews in Physics 13 (2025), 100120 (10.1016/j.revip.2025.100120, 2310.05673)
• E. Lupi et al. (P.V.), “Neuromorphic Readout for Hadron Calorimeters”, Particles 2025, 8(2) 52 (10.3390/particles8020052, 2502.12693)
• A. De Vita et al. (P.V.), “Hadron Identification Prospects With Granular Calorimeters”, Particles 2025, 8(2) 58 (10.3390/particles8020058 2502.10817)
• K. Schmidt et al. (P.V.), “End-to-End Detector Optimization with Diffusion models: A Case Study in Sampling Calorimeters”, Particles 2025, 8(2) 47 (10.3390/particles8020047, 2502.02152)
• P. Vischia, 2025, “AI-assisted design of experiments at the frontiers of computation: methods and new perspectives”, Proceedings of Science 476, ICHEP2024, 1022 (2025) (10.22323/1.476.1022)
• S. Sánchez Cruz, M. Kolosova, C. Ramón Álvarez, G. Petrucciani, P. Vischia, 2024, “Equivariant neural networks for robust CP observables”, Phys. Rev. D 110, 096023 (10.1103/PhysRevD.110.096023);
• T. Dorigo et al. (P.V.), “Artificial Intelligence in Science and Society: The Vision of USERN”, IEEE Access 2025 (13) 15993-16054, 10.1109/ACCESS.2025.3529357

Ten Selected publications

• T. Dorigo, A. Giammanco, P. Vischia (eds.) et al., 2023, “Toward the end-to-end optimization of particle physics instruments with differentiable programming”, Reviews in Physics, 10, 100085 (2023) (10.1016/j.revip.2023.100085)
• G. Baydin, K. Cranmer, P. de Castro,…, H. Yarar (17 authors, alphabetical order), 2021, “Toward Machine Learning Optimization of Experimental Design”, Nuclear Physics News 31, 01 (2021) (10.1080/10619127.2021.1881364);
• A. Stakia, T. Dorigo, G. Banelli, …, A. Weiler (25 authors, first two corresponding, last 23 in alphabetical order), 2021, “Advances in Multi-Variate Analysis Methods for New Physics Searches at the Large Hadron Collider”, Reviews in Physics, 7 100063 (2021) (10.1016/j.revip.2021.100063);
• The CMS Collaboration (alphabetical order), 2021, “Measurement of the Higgs boson production rate in association with top quarks in final states with electrons, muons, and hadronically decaying tau leptons at sqrt(s)=13 TeV”, Eur. Phys. J. C 81, 378.
• P. Vischia, 2020, “Reporting results in High Energy Physics publications: A manifesto“, Reviews in Physics 5, 100046 (2020) (10.1016/j.revip.2020.100046);
• The CMS Collaboration (alphabetical order), 2019, “Measurements of the pp→WZ inclusive and differential production cross sections and constraints on charged anomalous triple gauge couplings at sqrt(s)=13 TeV”, J. High Energ. Phys. 2019, 122 (10.1007/JHEP04(2019)122);
• The CMS Collaboration (alphabetical order), 2018, “Observation of ttH production”, Phys. Rev. Lett. 120, 231801 (10.1103/PhysRevLett.120.231801);
• The CMS Collaboration (alphabetical order), 2018, “Evidence for associated production of a Higgs boson with a top quark pair in final states with electrons, muons, and hadronically decaying tau leptons at sqrt(s)=13 TeV”, J. High Energ. Phys. 2018, 66 (10.1007/JHEP08(2018)066);
• P. Vischia, T. Dorigo, 2017, “The Inverse Bagging Algorithm: Anomaly Detection by Inverse Bootstrap Aggregating”, EPJ WoC 137, 11009 (2017) (10.1051/epjconf/201713711009);
• The CMS Collaboration (alphabetical order), 2012, “Measurement of the top quark mass in ttbar events with dilepton final states in pp collisions at sqrt(s)=7 TeV”, Eur. Phys. J. C 72, 2202 (2012) (10.1140/epjc/s10052-012-2202-z).