Matteo Cremonesi

According to our database, Matteo Cremonesi authored at least 8 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

DGNNFlow: A Streaming Dataflow Architecture for Real-Time Edge-based Dynamic GNN Inference in HL-LHC Trigger Systems.

Davendra Maharaj, Tu Pham, Peter Meiring, Kyungmin Park, Sena Durgut, Cong Hao, Matteo Cremonesi

CoRR, March, 2026

Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP).

Julia Gonski, Jenni Ott, Shiva Abbaszadeh, Sagar Addepalli, Matteo Cremonesi, Jennet Dickinson, Giuseppe Di Guglielmo, Erdem Yigit Ertorer, Lindsey Gray, Ryan Herbst, Christian Herwig, Tae Min Hong, Benedikt Maier, Maryam Bayat Makou, David Miller, Mark S. Neubauer, Cristián Peña, Dylan Rankin, Seon-Hee Seo, Giordon Stark, Alexander Tapper, Audrey Corbeil Therrien, Ioannis Xiotidis, Keisuke Yoshihara, G. Abarajithan, Nural Akchurin, Carlos Argüelles, Saptaparna Bhattacharya, Lorenzo Borella, Christian Boutan, Tom Braine, James Brau, Martin Breidenbach, Antonio Chahine, Talal Ahmed Chowdhury, Yuan-Tang Chou, Seokju Chung, Alberto Coppi, Mariarosaria D'Alfonso, Abhilasha Dave, Chance Desmet, Angela Di Fulvio, Karri DiPetrillo, Javier Duarte, Auralee Edelen, Jan Eysermans, Yongbin Feng, Emmett Forrestel, Dolores Garcia, Loredana Gastaldo, Julián García Pardiñas, Lino Gerlach, Loukas Gouskos, Katya Govorkova, Carl Grace, Christopher Grant, Philip Harris, Ciaran Hasnip, Timon Heim, Abraham Holtermann, Gian Michele Innocenti, Koji Ishidoshiro, Miaochen Jin, Jyothisraj Johnson, Stephen Jones, Andreas Jung, Georgia Karagiorgi, Ryan Kastner, Nicholas Kamp, Doojin Kim, Kyoungchul Kong, Katie Kudela, Jelena Lalic, Bo-Cheng Lai, Yun-Tsung Lai, Tommy Lam, Jeffrey Lazar, Aobo Li, Zepeng Li, Haoyun Liu, Vladimir Loncar, Luca Macchiarulo, Christopher Madrid, Zhenghua Ma, Prashansa Mukim, Victoria Nguyen, Sungbin Oh, Isobel Ojalvo, Hideyoshi Ozaki, Simone Pagan Griso, Myeonghun Park, Christoph Paus, Santosh Parajuli, Benjamin Parpillon, Sara Pozzi, Ema Puljak

CoRR, February, 2026

2025

FastGraph: Optimized GPU-Enabled Algorithms for Fast Graph Building and Message Passing.

Aarush Agarwal, Raymond He, Jan Kieseler, Matteo Cremonesi, Shah Rukh Qasim

CoRR, November, 2025

Building Machine Learning Challenges for Anomaly Detection in Science.

Elizabeth G. Campolongo, Yuan-Tang Chou, Ekaterina Govorkova, Wahid Bhimji, Wei-Lun Chao, Chris Harris, Shih-Chieh Hsu, Hilmar Lapp, Mark S. Neubauer, Josephine M. Namayanja, Aneesh Subramanian, Philip C. Harris, Advaith Anand, David Edward Carlyn, Subhankar Ghosh, Christopher G. Lawrence, Eric A. Moreno, Ryan Raikman, Jiaman Wu, Ziheng Zhang, Bayu Adhi, Mohammad Ahmadi Gharehtoragh, Saúl Alonso-Monsalve, Marta Babicz, Furqan Baig, Namrata Banerji, William Bardon, Tyler Barna, Tanya Y. Berger-Wolf, Adji Bousso Dieng, Micah Brachman, Quentin Buat, David C. Y. Hui, Phuong Cao, Franco Cerino, Yi-Chun Chang, Shivaji Chaulagain, An-Kai Chen, Deming Chen, Eric Chen, Chia-Jui Chou, Zih-Chen Ciou, Miles Cochran-Branson, Artur Cordeiro Oudot Choi, Michael Coughlin, Matteo Cremonesi, Maria Dadarlat, Peter Darch, Malina Desai, Daniel Diaz, Steven Dillmann, Javier M. Duarte, Isla Duporge, Urbas Ekka, Saba Entezari Heravi, Hao Fang, Rian Flynn, Geoffrey Fox, Emily Freed, Hang Gao, Jing Gao, Julia Gonski, Matthew J. Graham, Abolfazl Hashemi, Scott Hauck, James Hazelden, Joshua Henry Peterson, Duc Hoang, Wei Hu, Mirco Hünnefeld, David Hyde, Vandana P. Janeja, Nattapon Jaroenchai, Haoyi Jia, Yunfan Kang, Maksim Kholiavchenko, Elham E Khoda, Sangin Kim, Aditya Kumar, Bo-Cheng Lai, Trung Le, Chi-Wei Lee, JangHyeon Lee, Shaocheng Lee, Suzan van der Lee, Charles Lewis, Haitong Li, Haoyang Li, Henry Liao, Mia Liu, Xiaolin Liu, Xiulong Liu, Vladimir Loncar, Fangzheng Lyu, Ilya Makarov, Abhishikth Mallampalli Chen-Yu Mao, Alexander Michels, Alexander Migala, Farouk Mokhtar, Mathieu Morlighem

CoRR, March, 2025

2020

Coffea - Columnar Object Framework For Effective Analysis.

Nicholas Smith, Lindsey Gray, Matteo Cremonesi, Bo Jayatilaka, Oliver Gutsche, Allison Hall, Kevin Pedro, Maria Acosta Flechas, Andrew Melo, Stefano Belforte, Jim Pivarski

CoRR, 2020

2019

Using Big Data Technologies for HEP Analysis.

Matteo Cremonesi, Claudio Bellini, Bianny Bian, Luca Canali, Vasileios Dimakopoulos, Peter Elmer, Ian Fisk, Maria Girone, Oliver Gutsche, Siew-Yan Hoh, Bo Jayatilaka, Viktor Khristenko, Andrea Luiselli, Andrew Melo, Evangelos Motesnitsalis, Dominick Olivito, Jacopo Pazzini, Jim Pivarski, Alexey Svyatkovskiy, Marco Zanetti

CoRR, 2019

2017

CMS Analysis and Data Reduction with Apache Spark.

Oliver Gutsche, Luca Canali, Illia Cremer, Matteo Cremonesi, Peter Elmer, Ian Fisk, Maria Girone, Bo Jayatilaka, Jim Kowalkowski, Viktor Khristenko, Evangelos Motesnitsalis, Jim Pivarski, Saba Sehrish, Kacper Surdy, Alexey Svyatkovskiy

CoRR, 2017

Big Data in HEP: A comprehensive use case study.

Oliver Gutsche, Matteo Cremonesi, Peter Elmer, Bo Jayatilaka, Jim Kowalkowski, Jim Pivarski, Saba Sehrish, Cristina Mantilla Suarez, Alexey Svyatkovskiy, Nhan Tran

CoRR, 2017