Samuel V. Scarpino

20 papers A* 1Journal 18Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Hypergraph representations of single-cell RNA sequencing data for improved cell clustering. Bioinform. Wan He, Daniel I. Bolnick, Samuel V. Scarpino, Tina Eliassi-Rad
2025	J	`jnl`	Artificial intelligence for modelling infectious disease epidemics. Nat. Moritz U. G. Kraemer, Joseph L.-H. Tsui, Serina Chang, Spyros Lytras, Mark P. Khurana, Samantha Vanderslott, Sumali Bajaj, Neil Scheidwasser, Jacob Liam Curran-Sebastian, Elizaveta Semenova, Mengyan Zhang, H. Juliette T. Unwin, Oliver J. Watson, Cathal Mills, Abhishek Dasgupta, Luca Ferretti, Samuel V. Scarpino, Etien Koua, Oliver Morgan, Houriiyah Tegally, Ulrich Paquet, Loukas Moutsianas, Christophe Fraser, Neil M. Ferguson, Eric J. Topol, David A. Duchêne, Tanja Stadler, Patricia Kingori, Michael J. Parker, Francesca Dominici, Nigel Shadbolt, Marc A. Suchard, Oliver Ratmann, Seth R. Flaxman, Edward C. Holmes, Manuel Gomez-Rodriguez, Bernhard Schölkopf, Christl A. Donnelly, Oliver G. Pybus, Simon Cauchemez, Samir Bhatt
2025	J	`jnl`	Computational frame analysis revisited: On LLMs for studying news coverage. CoRR Sharaj Kunjar, Alyssa Hasegawa Smith, Tyler R. Mckenzie, Rushali Mohbe, Samuel V. Scarpino, Brooke Foucault Welles
2025	J	`jnl`	Deterministic construction of typical networks in network models. CoRR Narayan G. Sabhahit, Moritz Laber, Harrison Hartle, Jasper van der Kolk, Samuel V. Scarpino, Brennan Klein, Dmitri V. Krioukov
2024	J	`jnl`	A Misclassification Network-Based Method for Comparative Genomic Analysis. CoRR Wan He, Tina Eliassi-Rad, Samuel V. Scarpino
2023	J	`jnl`	The Role of Directionality, Heterogeneity, and Correlations in Epidemic Risk and Spread. SIAM Rev. Antoine Allard, Cristopher Moore, Samuel V. Scarpino, Benjamin M. Althouse, Laurent Hébert-Dufresne
2022	J	`jnl`	A Family of Fitness Landscapes Modeled through Gene Regulatory Networks. Entropy Chia-Hung Yang, Samuel V. Scarpino
2022	J	`jnl`	Effective resistance against pandemics: Mobility network sparsification for high-fidelity epidemic simulations. PLoS Comput. Biol. Alexander M. Mercier, Samuel V. Scarpino, Cristopher Moore
2021	J	`jnl`	Data curation during a pandemic and lessons learned from COVID-19. Nat. Comput. Sci. Moritz U. G. Kraemer, Samuel V. Scarpino, Vukosi Marivate, Bernardo Gutierrez, Bo Xu, Graham Lee, Jared B. Hawkins, Caitlin M. Rivers, David M. Pigott, Rebecca Katz, John S. Brownstein
2021	J	`jnl`	Development and Validation of Manually Modified and Supervised Machine Learning Clinical Assessment Algorithms for Malaria in Nigerian Children. Frontiers Artif. Intell. Megan McLaughlin, Karell G. Pellé, Samuel V. Scarpino, Aisha Giwa, Ezra Mount-Finette, Nada Haidar, Fatima Adamu, Nirmal Ravi, Adam Thompson, Barry Heath, Sabine Dittrich, Barry Finette
2021	J	`jnl`	Effective Resistance for Pandemics: Mobility Network Sparsification for High-Fidelity Epidemic Simulation. CoRR Alexander M. Mercier, Samuel V. Scarpino, Cristopher Moore
2021	—	`conf`	Networked data and COVID-19. GRADES-NDA@SIGMOD Samuel V. Scarpino
2020	A*	`conf`	Fighting a Pandemic: Convergence of Expertise, Data Science and Policy. KDD Tina Eliassi-Rad, Nitesh V. Chawla, Vittoria Colizza, Lauren Gardner, Marcel Salathé, Samuel V. Scarpino, Joseph T. Wu
2020	J	`jnl`	Mobile phone data and COVID-19: Missing an opportunity? CoRR Nuria Oliver, Emmanuel Letouzé, Harald Sterly, Sébastien Delataille, Marco De Nadai, Bruno Lepri, Renaud Lambiotte, Richard Benjamins, Ciro Cattuto, Vittoria Colizza, Nicolas de Cordes, Samuel P. Fraiberger, Till Koebe, Sune Lehmann, Juan Murillo, Alex Pentland, Phuong N. Pham, Frédéric Pivetta, Albert Ali Salah, Jari Saramäki, Samuel V. Scarpino, Michele Tizzoni, Stefaan Verhulst, Patrick Vinck
2020	J	`jnl`	Socioeconomic bias in influenza surveillance. PLoS Comput. Biol. Samuel V. Scarpino, James G. Scott, Rosalind M. Eggo, Bruce Clements, Nedialko B. Dimitrov, Lauren Ancel Meyers
2018	J	`jnl`	The Interhospital Transfer Network for Very Low Birth Weight Infants in the United States. CoRR Munik Shrestha, Samuel V. Scarpino, Erika M. Edwards, Lucy T. Greenberg, Jeffrey D. Horbar
2018	J	`jnl`	The interhospital transfer network for very low birth weight infants in the United States. EPJ Data Sci. Munik Shrestha, Samuel V. Scarpino, Erika M. Edwards, Lucy T. Greenberg, Jeffrey D. Horbar
2015	J	`jnl`	A message-passing approach for recurrent-state epidemic models on networks. CoRR Munik Shrestha, Samuel V. Scarpino, Cristopher Moore
2015	J	`jnl`	Enhancing disease surveillance with novel data streams: challenges and opportunities. EPJ Data Sci. Benjamin M. Althouse, Samuel V. Scarpino, Lauren Ancel Meyers, John W. Ayers, Marisa Bargsten, Joan Baumbach, John S. Brownstein, Lauren A. Castro, Hannah E. Clapham, Derek A. T. Cummings, Sara Y. Del Valle, Stephen G. Eubank, Geoffrey Fairchild, Lyn Finelli, Nicholas Generous, Dylan B. George, David R. Harper, Laurent Hébert-Dufresne, Michael A. Johansson, Kevin J. Konty, Marc Lipsitch, Gabriel Milinovich, Joseph D. Miller, Elaine O. Nsoesie, Donald R. Olson, Michael J. Paul, Philip M. Polgreen, Reid Priedhorsky, Jonathan M. Read, Isabel Rodríguez-Barraquer, Derek J. Smith, Christian Stefansen, David L. Swerdlow, Deborah Thompson, Alessandro Vespignani, Amy Wesolowski
2012	J	`jnl`	Optimizing Provider Recruitment for Influenza Surveillance Networks. PLoS Comput. Biol. Samuel V. Scarpino, Nedialko B. Dimitrov, Lauren Ancel Meyers

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.