Publications

Below is a concise list of relevant publications to the research interests of the MODE Collaboration. MODE members among the authors are indicated in boldface:

Andrea Svizzeretto, Mateusz Bawaj (2026). Partial Observability and Domain Randomization in RL-Based Strategy for Optical Cavity Locking Optimization. PoS.

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Tommaso Dorigo, Pietro Vischia, Shahzaib Abbas, Tosin Adewumi, Lama Alkhaled, Lorenzo Arsini, Muhammad Awais, Maxim Borisyak, András Bóta, Florian Bury, Sascha Caron, James Carzon, Long Chen, Prakash C. Chhipa, Paul Christakopoulos, Jacopo De Piccoli, Andrea De Vita, Zlatan Dimitrov, Michele Doro, Luigi Favaro, Francesco Ferranti, Santiago Folgueras, Rihab Gargouri, Nicolas Gauger, Andrea Giammanco, Christian Glaser, Tobias Golling, João A. Gonçalves, Hui Han, Hamza Hanif, Lukas Heinrich, Yan Chai Hum, Florent Imbert, Andreas Ipp, Michael Kagan, Noor Kainat Syeda, Rukshak Kapoor, Aparup Khatua, Eduard J. Kerkhoven, Jan Kieseler, Tobias Kortus, Ashish Kumar Singh, Marius S. Köppel, Daniel Lanchares, Ann Lee, Pelayo Leguina, Christos Leonidopoulos, Giuseppe Levi, Boying Li, Chang Liu, Marcus Liwicki, Karl Lowenmark, Enrico Lupi, Carlo Mancini-Terracciano, Dominik Maršík, Leonidas Matsakas, Hamam Mokayed, Federico Nardi, Amirhossein Nayebiastaneh, Xuan T. Nguyen, Aitor Orio, Jingjing Pan, Jigar Patel, Carmelo Pellegrino, María Pereira Martínez, Karolos Potamianos, Shah Rukh Qasim, Martin Ravn, Luis Recabarren Vergara, Humberto Reyes-González, Hipolito A. Riveros Guevara, Ippocratis D. Saltas, Rajkumar Saini, Fredrik Sandin, Alexander Schilling, Kylian Schmidt, Nicola Serra, Saqib Shahzad, Foteini Simistira Liwicki, Giles C. Strong, Kristian Tchiorniy, Mia Tosi, Andrey Ustyuzhanin, Xabier Cid Vidal, Kinga A. Wozniak, Mengqing Wu, Zahraa Zaher (2026). On the Codesign of Scientific Experiments and Industrial Systems.

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Konstantin Nikolaevich Borozdin, Ralitza Vozdolska (2026). Imaging Techniques in Muon Scattering Tomography. PoS.

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Mohamed Aly, Lino Gerlach (2026). Differentiating a HEP Analysis Pipeline within the Scikit-HEP Software Ecosystem. PoS.

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Xuan Tung Nguyen, Long Chen, Tommaso Dorigo, Nicolas Gauger, Pietro Vischia, Federico Nardi, Muhammad Awais, Hamza Hanif, Shahzaib Abbas, Rukshak Kapoor (2026). Differentiable Surrogate for Detector Simulation and Design with Diffusion Models.

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Cyril Martin Alispach, Matthieu Heller, Teresa Montaruli (2026). Design of an Imaging Air Cherenkov Telescope array layout with differential programming. PoS.

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Max Aehle, Lorenzo Arsini, R. Belén Barreiro, Anastasios Belias, Alexey Boldyrev, Florian Bury, Susana Cebrian, Alexander Demin, Jennet Dickinson, Julien Donini, Tommaso Dorigo, Michele Doro, Nicolas Gauger, Andrea Giammanco, Lindsey Gray, Borja S. González, Verena Kain, Jan Kieseler, Lisa Kusch, Marcus Liwicki, Gernot Maier, Federico Nardi, Fedor Ratnikov, Ryan Roussel, Roberto Ruiz De Austri, Fredrik Sandin, Michael Schenk, Bruno Scarpa, Pedro Silva, Giles C. Strong, Pietro Vischia (2025). Progress in end-to-end optimization of fundamental physics experimental apparata with differentiable programming. Reviews in Physics.

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Tommaso Dorigo, Max Aehle, Cornelia Arcaro, Muhammad Awais, Fabiola Bergamaschi, Julien Donini, Michele Doro, Nicolas Gauger, Rafael Izbicki, Jan Kieseler, Ann Lee, Luca Masserano, Federico Nardi, Raaghav Rajesh, Luis Recabarren Vergara, Alexander Shen (2025). Toward the end-to-end optimization of the SWGO array layout. Nuclear Physics B.

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Andrea De Vita, Abhishek, Max Aehle, Muhammad Awais, Alessandro Breccia, Riccardo Carroccio, Long Chen, Tommaso Dorigo, Nicolas Gauger, Ralf Keidel, Jan Kieseler, Enrico Lupi, Federico Nardi, Xuan Tung Nguyen, Fredrik Sandin, Kylian Schmidt, Pietro Vischia, Joseph Willmore (2025). Hadron Identification Prospects with Granular Calorimeters. Particles.

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Francisco Hervás Álvarez, Alberto Valero Biot, Luca Fiorini, Héctor Gutiérrez Arance, Fernando Carrió, Sonakshi Ahuja, Francesco Curcio (2025). Versal Adaptive Compute Acceleration Platform Processing for ATLAS-TileCal Signal Reconstruction. Particles.

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Emanuele Coradin, Fabio Cufino, Muhammad Awais, Tommaso Dorigo, Enrico Lupi, Eleonora Porcu, Jinu Raj, Fredrik Sandin, Mia Tosi (2025). Unsupervised Particle Tracking with Neuromorphic Computing. Particles.

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Florian Bury, Maxime Lagrange (2025). Scattering-Based Machine Learning Algorithms for Momentum Estimation in Muon Tomography. Particles.

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Samuel Escrig, Christophe Rappold (2025). Production Optimization of Exotic Hypernuclei via Heavy-Ion Beams at GSI-FAIR. Particles.

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Héctor Gutiérrez Arance, Luca Fiorini, Alberto Valero Biot, Francisco Hervás Álvarez, Santiago Folgueras, Carlos Vico Villalba, Pelayo Leguina López, Arantza Oyanguren Campos, Valerii Kholoimov, Volodymyr Svintozelskyi, Jiahui Zhuo (2025). Porting MADGRAPH to FPGA Using High-Level Synthesis (HLS). Particles.

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Martin Langgård Ravn, Philipp Pilar, Christian Glaser, Niklas Wahlström, Thorsten Glüsenkamp (2025). Optimization pipeline for in-ice radio neutrino detectors. PoS.

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Zahraa Zaher, Samuel Alvarez, Tommaso Dorigo, Andrea Giammanco, Maxime Lagrange, Giles C. Strong, Pietro Vischia, Haitham Zaraket (2025). Optimisation of Muon Tomography Scanners for Border Control Using TomOpt. Particles.

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Enrico Lupi, Abhishek, Max Aehle, Muhammad Awais, Alessandro Breccia, Riccardo Carroccio, Long Chen, Abhijit Das, Andrea De Vita, Tommaso Dorigo, Nicolas Ralph Gauger, Ralf Keidel, Jan Kieseler, Anders Mikkelsen, Federico Nardi, Xuan Tung Nguyen, Fredrik Sandin, Kylian Schmidt, Pietro Vischia, Joseph Willmore (2025). Neuromorphic Readout for Hadron Calorimeters. Particles.

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William O’Donnell, David Mahon, Guangliang Yang, Simon Gardner (2025). Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications. Particles.

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Luca Castelli (2025). Machine Learning Approach to Shield Optimization at Muon Collider. Particles.

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Martin Erdmann, Frederik Krieger, Alex Reuzki, Josina Schulte, Michael Smolka, Maximilian Straub (2025). Information Field Theory for Two Applications in Astroparticle Physics. Particles.

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Andrea De Vita, Abhishek, Max Aehle, Muhammad Awais, Alessandro Breccia, Riccardo Carroccio, Long Chen, Tommaso Dorigo, Nicolas Gauger, Ralf Keidel, Jan Kieseler, Enrico Lupi, Federico Nardi, Xuan Tung Nguyen, Fredrik Sandin, Kylian Schmidt, Pietro Vischia, Joseph Willmore (2025). Hadron Identification Prospects with Granular Calorimeters. Particles.

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Jean-Marco Alameddine, Felix Sattler, Maurice Stephan, Sarah Barnes (2025). Gradient-descent-based reconstruction for muon tomography based on automatic differentiation in PyTorch. PoS.

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Felix Sattler, Jean-Marco Alameddine, Ángel Bueno Rodriguez, Maurice Stephan, Sarah Barnes (2025). From Light to Muons: Towards a Unified Framework for Physics-based 3D Scene Reconstruction. PoS.

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Kylian Schmidt, Krishna Nikhil Kota, Jan Kieseler, Andrea De Vita, Markus Klute, Abhishek, Max Aehle, Muhammad Awais, Alessandro Breccia, Riccardo Carroccio, Long Chen, Tommaso Dorigo, Nicolas Gauger, Enrico Lupi, Federico Nardi, Xuan Tung Nguyen, Fredrik Sandin, Joseph Willmore, Pietro Vischia (2025). End-to-End Detector Optimization with Diffusion Models: A Case Study in Sampling Calorimeters. Particles.

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Kylian Schmidt, Nikhil Kota, Jan Kieseler, Andrea De Vita, Markus Klute, Abhishek, Max Aehle, Muhammad Awais, Alessandro Breccia, Riccardo Carroccio, Long Chen, Tommaso Dorigo, Nicolas Gauger, Enrico Lupi, Federico Nardi, Xuan Tung Nguyen, Fredrik Sandin, Joseph Willmore, Pietro Vischia (2025). End-to-End Detector Optimization with Diffusion models: A Case Study in Sampling Calorimeters.

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Galo Gallardo Romero, Guillermo Rodríguez-Llorente, Lucas Magariños Rodríguez, Rodrigo Morant Navascués, Nikita Khvatkin Petrovsky, Rubén Lorenzo Ortega, Roberto Gómez-Espinosa Martín (2025). Differentiable Deep Learning Surrogate Models Applied to the Optimization of the IFMIF-DONES Facility. Particles.

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Kalina Dimitrova, Venelin Kozhuharov, Peicho Petkov (2025). Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors. Particles.

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Bruno Jorge De Matos Rodrigues, Ines Ochoa, Agostinho Gomes (2025). Design optimization of hadronic calorimeters for future colliders. PoS.

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Christina Koutsou, Vassil Vassilev, David Lange (2025). Bringing Automatic Differentiation to CUDA with Compiler-Based Source Transformations. PoS.

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Marta De La Puente Santos, Zahraa Zaher, Maxime Lagrange, Andrea Giammanco, Pietro Vischia (2025). Bias Reduction Using Expectation Maximization in the Optimization of an AI-Assisted Muon Tomography System. PoS.

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María Pereira Martínez, Xabier Cid Vidal, Pietro Vischia (2025). Automatic Optimization of a Parallel-Plate Avalanche Counter with Optical Readout. Particles.

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Pietro Vischia (2025). AI-assisted design of experiments at the frontiers of computation: methods and new perspectives. Proceedings of 42nd International Conference on High Energy Physics — PoS(ICHEP2024).

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Burak Bilki (2025). A Multiple Readout Ultra-High Segmentation Detector Concept For Future Colliders. PoS.

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Giles C Strong, Maxime Lagrange, Aitor Orio, Anna Bordignon, Florian Bury, Tommaso Dorigo, Andrea Giammanco, Mariam Heikal, Jan Kieseler, Max Lamparth, Pablo Martínez Ruíz Del Árbol, Federico Nardi, Pietro Vischia, Haitham Zaraket (2024). TomOpt: differential optimisation for task- and constraint-aware design of particle detectors in the context of muon tomography. Machine Learning: Science and Technology.

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Max Aehle, Mihály Novák, Vassil Vassilev, Nicolas Gauger, Lukas Heinrich, Michael Kagan, David Lange (2024). Optimization Using Pathwise Algorithmic Derivatives of Electromagnetic Shower Simulations.

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Nathan Simpson, Lukas Heinrich (2023). neos: End-to-End-Optimised Summary Statistics for High Energy Physics. Journal of Physics: Conference Series.

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Lukas Heinrich, Michael Kagan (2023). Differentiable Matrix Elements with MadJax. Journal of Physics: Conference Series.

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Michael Kagan, Lukas Heinrich (2023). Branches of a Tree: Taking Derivatives of Programs with Discrete and Branching Randomness in High Energy Physics.

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Tommaso Dorigo, Andrea Giammanco, Pietro Vischia, Max Aehle, Mateusz Bawaj, Alexey Boldyrev, Pablo De Castro Manzano, Denis Derkach, Julien Donini, Auralee Edelen, Federica Fanzago, Nicolas Gauger, Christian Glaser, Atılım G. Baydin, Lukas Heinrich, Ralf Keidel, Jan Kieseler, Claudius Krause, Maxime Lagrange, Max Lamparth, Lukas Layer, Gernot Maier, Federico Nardi, Helge E. S. Pettersen, Alberto Ramos, Fedor Ratnikov, Dieter Röhrich, Roberto Ruiz De Austri, Pablo Martínez Ruiz Del Árbol, Oleg Savchenko, Nathan Simpson, Giles C. Strong, Angela Taliercio, Mia Tosi, Andrey Ustyuzhanin, Haitham Zaraket (2022). Toward the End-to-End Optimization of Particle Physics Instruments with Differentiable Programming: a White Paper.

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Coralie Neubüser, Jan Kieseler, Paul Lujan (2022). Optimising longitudinal and lateral calorimeter granularity for software compensation in hadronic showers using deep neural networks. The European Physical Journal C.

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T. Dorigo, Sofia Guglielmini, Jan Kieseler, Lukas Layer, Giles C. Strong (2022). Deep Regression of Muon Energy with a K-Nearest Neighbor Algorithm.

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Jan Kieseler, Giles C. Strong, Filippo Chiandotto, Tommaso Dorigo, Lukas Layer (2022). Calorimetric Measurement of Multi-TeV Muons via Deep Regression. The European Physical Journal C.

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Atılım Güneş Baydin, Kyle Cranmer, Pablo De Castro Manzano, Christophe Delaere, Denis Derkach, Julien Donini, Tommaso Dorigo, Andrea Giammanco, Jan Kieseler, Lukas Layer, Gilles Louppe, Fedor Ratnikov, Giles C. Strong, Mia Tosi, Andrey Ustyuzhanin, Pietro Vischia, Hevjin Yarar (2021). Toward Machine Learning Optimization of Experimental Design. Nuclear Physics News.

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Jan Kieseler (2020). Object condensation: one-stage grid-free multi-object reconstruction in physics detectors, graph, and image data. The European Physical Journal C.

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Kyle Cranmer, Johann Brehmer, Gilles Louppe (2020). The frontier of simulation-based inference. Proceedings of the National Academy of Sciences.

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Fedor Ratnikov, Denis Derkach, Alexey Boldyrev, Andrey Shevelev, Pavel Fakanov, Leonid Matyushin (2020). Using machine learning to speed up new and upgrade detector studies: a calorimeter case. EPJ Web of Conferences.

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Tommaso Dorigo, Jan Kieseler, Lukas Layer, Giles Strong (2020). Muon Energy Measurement from Radiative Losses in a Calorimeter for a Collider Detector.

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Alexey Boldyrev, Denis Derkach, Fedor Ratnikov, Andrey Shevelev (2020). ML-assisted versatile approach to Calorimeter R&D. JINST.

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Johann Brehmer, Felix Kling, Irina Espejo, Kyle Cranmer (2020). MadMiner: Machine learning-based inference for particle physics. Comput. Softw. Big Sci..

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Tommaso Dorigo (2020). Geometry optimization of a muon-electron scattering detector. Physics Open.

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Sergey Shirobokov, Vladislav Belavin, Michael Kagan, Andrey Ustyuzhanin, Atilim Güneş Baydin (2020). Black-box optimization with local generative surrogates. Proceedings of the 34th International Conference on Neural Information Processing Systems.

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Gilles Louppe, Joeri Hermans, Kyle Cranmer (2020). Adversarial Variational Optimization of Non-Differentiable Simulators.

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Pablo De Castro, Tommaso Dorigo (2019). INFERNO: Inference-Aware Neural Optimisation. Computer Physics Communications.

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Sophie Wuyckens, Andrea Giammanco, Eduardo Cortina Gil, Pavel Demin (2018). A portable muon telescope based on small and gas-tight resistive plate chambers. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

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Atılım Günes Baydin, Barak A. Pearlmutter, Alexey Andreyevich Radul, Jeffrey Mark Siskind (2017). Automatic differentiation in machine learning: a survey. J. Mach. Learn. Res..

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Kyle Cranmer, Juan Pavez, Gilles Louppe (2016). Approximating Likelihood Ratios with Calibrated Discriminative Classifiers.

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P. Giubilato, W. Snoeys, S. Mattiazzo, N. Pozzobon, D. Pantano, D. Bisello, T. Kugathasan, J. Rousset, H. Mugnier, C.A. Marin Tobon (2015). iMPACT: Innovative pCT scanner. 2015 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC).

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