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Physics & X-Ray Science Computing

Paolo Calafiura

IMG 5194
Paolo Calafiura
Senior Scientist
Group Lead
Phone: +1 510 486 6717

Biographical Sketch

Paolo Calafiura is a computational physicist in the Physics and X-Ray Science Computing Group which he also leads. He works on software frameworks, tools, and methods for high-energy and nuclear physics experiments. Currently, he is the US Computing and Software operations manager for the ATLAS experiment at CERN. He is also co-PI of the HEP Center for Computational Excellence. His research interests include portable data models, distributed workflows scheduling, and pattern recognition methods for noisy experimental data.

 

Books

Paolo Calafiura and others, Artificial Intelligence for High Energy Physics, edited by Paolo Calafiura, David Rousseau, Kazuhiro Terao, (World Scientific: March 1, 2022) doi: 10.1142/12200

Presentation/Talks

John Wu, Ben Brown, Paolo Calafiura, Quincey Koziol, Dongeun Lee, Alex Sim, Devesh Tiwari, Support for In-Flight Data Analyses in Scientific Workflows, DOE ASCR Workshop on the Management and Storage of Scientific Data, 2022, doi: 10.2172/1843500

Others

Christopher D. Jones, Kyle Knoepfel, Paolo Calafiura, Charles Leggett, Vakhtang Tsulaia, Evolution of HEP Processing Frameworks, 2022 Snowmass Summer Study, 2022,

Savannah Thais, Paolo Calafiura, Grigorios Chachamis, Gage DeZoort, Javier Duarte, Sanmay Ganguly, Michael Kagan, Daniel Murnane, Mark S. Neubauer, Kazuhiro Terao, Graph Neural Networks in Particle Physics: Implementations, Innovations, and Challenges, 2022 Snowmass Summer Study, 2022,

Meghna Bhattacharya, others, Portability: A Necessary Approach for Future Scientific Software, 2022 Snowmass Summer Study, 2022,

Sunanda Banerjee, others, Detector and Beamline Simulation for Next-Generation High Energy Physics Experiments, 2022 Snowmass Summer Study, 2022,

Chun-Yi Wang, others, Reconstruction of Large Radius Tracks with the Exa.TrkX pipeline, 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research: AI Decoded - Towards Sustainable, Diverse, Performant and Effective Scientific Computing, 2022,

Alina Lazar, others, Accelerating the Inference of the Exa.TrkX Pipeline, 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research: AI Decoded - Towards Sustainable, Diverse, Performant and Effective Scientific Computing, 2022,

Xiangyang Ju, others, Performance of a geometric deep learning pipeline for HL-LHC particle tracking, Eur. Phys. J. C, Pages: 876 2021, doi: 10.1140/epjc/s10052-021-09675-8

Frederic Bapst, Wahid Bhimji, Paolo Calafiura, Heather Gray, Wim Lavrijsen, Lucy Linder, Alex Smith, A pattern recognition algorithm for quantum annealers, Comput. Softw. Big Sci., Pages: 1 2020, doi: 10.1007/s41781-019-0032-5

Masahiko Saito, Paolo Calafiura, Heather Gray, Wim Lavrijsen, Lucy Linder, Yasuyuki Okumura, Ryu Sawada, Alex Smith, Junichi Tanaka, Koji Terashi, Quantum annealing algorithms for track pattern recognition, EPJ Web Conf., Pages: 10006 2020, doi: 10.1051/epjconf/202024510006

Miha Muskinja, Paolo Calafiura, Charles Leggett, Illya Shapoval, Vakho Tsulaia, Raythena: a vertically integrated scheduler for ATLAS applications on heterogeneous distributed resources, EPJ Web Conf., Pages: 05042 2020, doi: 10.1051/epjconf/202024505042

Philippe Canal, Elizabeth Sexton-Kennedy, Jonathan Madsen, Soon Yung Jun, Guilherme Lima, Paolo Calafiura, Yunsong Wang, Seth Johnson, Geant Exascale Pilot Project, EPJ Web Conf., Pages: 09015 2020, doi: 10.1051/epjconf/202024509015

Xiangyang Ju, others, Graph Neural Networks for Particle Reconstruction in High Energy Physics detectors, 33rd Annual Conference on Neural Information Processing Systems, 2020,

Illya Shapoval, Paolo Calafiura, Quantum Associative Memory in HEP Track Pattern Recognition, EPJ Web Conf., Pages: 01012 2019, doi: 10.1051/epjconf/201921401012