The ESRs of INSIGHTS have produced many state-of-the-art results as evidenced by the 70 papers and technical reports directly related to their work. These include development of novel statistical methods and tools, their implementation in software, and applications to a wide variety of problems in physics and to other fields. A few examples include:
• L. Brenner, P. Verschuuren, G. Cowan, et al., Comparison of unfolding methods using RooFitUnfold, International Journal of Modern Physics A, Vol. 35, No. 24, 2050145 (2020); e-print arXiv:1910.14654
• Tommaso Dorigo, Hevjing Yarar et al., RanBox: Anomaly Detection in the Copula Space, presentation at the 10th International Conference on New Frontiers in Physics (ICNFP 2021).
• Lukas Layer et al., “Clustering of experimental seismo-acoustic events using Self-Organizing Map (SOM)” Frontiers in Earth Science.
• A. Golovatiuk, G. De Lellis, A. Ustyuzhanin, Deep learning for Directional Dark Matter search, Journal of Physics: Conference Series, vol. 1525, 012108 (2020).
• V. Hafych, P. Eller, O. Schulz, A. Caldwell, Parallelizing MCMC Sampling via Space Partitioning, Statistics & Computing 32,56 (2022); e-print arXiv:2008.03098
• ATLAS Collaboration (R. Balasubramanian), ATLAS-CONF-2021-053, Combined measurements of Higgs boson, production and decay using up to 139 fb−1 of proton–proton collision data at √s =13 TeV collected with the ATLAS experiment (2021).
• N. Simpson et al., Neos-Neural End-to-End Optimised Summary Statistics, to appear in ACAT 2021 proceedings, IOP Conference series; arXiv:2203.05570 [physics.data-an] (2022).
• Victor Ananyev, Alexander Lincoln Read, Approximating the mode of the non-central chi-squared distribution, arXiv:2106.12267 [math.CA] (2021)
• Sitong An, Lorenzo Moneta, C++ Code Generation for Fast Inference of Deep Learning Models in ROOT/TMVA, contribution to ICHEP 2021, EPJ Web Conf., 251 (2021) 03040.
• ATLAS Collaboration (Serena Palazzo), Measurements of top-quark pair single- and double-differential cross-sections in the all-hadronic channel in pp collisions at √s = 13 TeV using the ATLAS detector, Journal of High Energy Physics volume 2021, 33 (2021)
The impact of the INSIGHTS ITN is most directly felt by the ESRs themselves, who begun working as physicists and data scientists in universities (Naples, Verona), and companies (Mercedes-Benz, logically.ai Hoverture, PlantingSpace). Those who are currently finishing their PhDs will soon follow along similar paths.
Most training events of the INSIGHTS ITN were open to a broad audience, attracting several tens to more than 100 participants, and in this way the impact of INSIGHTS extended far beyond the network. Training events supported by INSIGHTS continue beyond the end of the programme, including the Pan-European Advanced School of Statistics created by INSIGHTS partner DESY. INSIGHTS partners from fields such as climate science, volcanology and finance hosted secondments that gave ESRs training and experience in industry and led to mutually beneficial knowledge transfer.
Socio-economic impact of INSIGHTS also includes outreach through social media, science festivals and events with school groups that have helped raise the aspirations of a younger generation to enter into scientific fields.
