Publications

(2024). Modular Family Symmetry in F-Theory GUTs from the Bottom-up.

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(2024). Symbolic Regression for Beyond the Standard Model Physics.

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(2024). Jet substructure observables for jet quenching in quark gluon plasma: A machine learning driven analysis. SciPost Phys..

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(2023). Exploring parameter spaces with artificial intelligence and machine learning black-box optimization algorithms. Phys. Rev. D.

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(2022). Fitting a Collider in a Quantum Computer: Tackling the Challenges of Quantum Machine Learning for Big Datasets. Frontiers in Artificial Intelligence.

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(2021). Use of a generalized energy Mover's distance in the search for rare phenomena at colliders. Eur. Phys. J. C.

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(2021). Deep Learning for the classification of quenched jets. JHEP.

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(2020). Transferability of Deep Learning Models in Searches for New Physics at Colliders. Phys. Rev..

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(2018). Non-universal $Z'$ from fluxed GUTs. Phys. Lett..

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(2016). R-Parity violation in F-Theory. JHEP.

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(2016). Neutrino mass from M Theory SO(10). JHEP.

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(2016). MSSM from F-theory SU(5) with Klein Monodromy. Phys. Rev..

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(2015). SO(10) Grand Unification in M theory on a G2 manifold. Phys. Rev..

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