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Felea, D., Mamuzic, J., Maselek, R., Mavromatos, N. E., Mitsou, V. A., Pinfold, J. L., et al. (2020). Prospects for discovering supersymmetric long-lived particles with MoEDAL. Eur. Phys. J. C, 80(5), 431–12pp.
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Ellis, J., Gomez, M. E., Lola, S., Ruiz de Austri, R., & Shafi, Q. (2020). Confronting grand unification with lepton flavour violation, dark matter and LHC data. J. High Energy Phys., 09(9), 197–29pp.
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Begone, G., Deisenroth, M. P., Kim, J. S., Liem, S., Ruiz de Austri, R., & Welling, M. (2019). Accelerating the BSM interpretation of LHC data with machine learning. Phys. Dark Universe, 24, 100293–5pp.
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Amoroso, S., Caron, S., Jueid, A., Ruiz de Austri, R., & Skands, P. (2019). Estimating QCD uncertainties in Monte Carlo event generators for gamma-ray dark matter searches. J. Cosmol. Astropart. Phys., 05(5), 007–44pp.
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MoEDAL Collaboration(Acharya, B. et al), Bernabeu, J., Mamuzic, J., Mitsou, V. A., Papavassiliou, J., Ruiz de Austri, R., et al. (2019). Magnetic Monopole Search with the Full MoEDAL Trapping Detector in 13 TeV pp Collisions Interpreted in Photon-Fusion and Drell-Yan Production. Phys. Rev. Lett., 123(2), 021802–7pp.
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