Paul Monsarrat

12 papers C 3Journal 7Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Expert-guided multi-objective optimization: An efficient strategy for parameter estimation of biological systems with limited data. Biosyst. Léa Da Costa Fernandes, David Bernard, François Pérès, Paul Monsarrat, Béatrice Cousin, Sylvain Cussat-Blanc
2025	J	`jnl`	Effective data exploration through clustering of local attributive explanations. Inf. Syst. Elodie Escriva, Tom Lefrere, Manon Martin, Julien Aligon, Alexandre Chanson, Jean-Baptiste Excoffier, Nicolas Labroche, Chantal Soulé-Dupuy, Paul Monsarrat
2025	C	`conf`	Exploring Local Feature Influences with Hierarchical Explanation Trees. ADBIS Emmanuel Doumard, Julien Aligon, Paul Monsarrat, Nicolas Labroche, Alexandre Chanson
2025	J	`jnl`	auto-xFS: An explanation-based feature selection tool for more meaningful and trustworthy machine learning models. SoftwareX Haomiao Wang, Julien Aligon, Haoran Zhou, Chantal Soulé-Dupuy, Paul Monsarrat
2023	J	`jnl`	A quantitative approach for the comparison of additive local explanation methods. Inf. Syst. Emmanuel Doumard, Julien Aligon, Elodie Escriva, Jean-Baptiste Excoffier, Paul Monsarrat, Chantal Soulé-Dupuy
2023	—	`conf`	Data Exploration Based on Local Attribution Explanation: A Medical Use Case. ADBIS (Short Papers) Elodie Escriva, Emmanuel Doumard, Jean-Baptiste Excoffier, Julien Aligon, Paul Monsarrat, Chantal Soulé-Dupuy
2023	—	`conf`	Databases and Information Systems: Contributions from ADBIS 2023 Workshops and Doctoral Consortium. ADBIS (Short Papers) Adam Przybylek, Aleksandra Karpus, Allel Hadjali, Anton Dignös, Carmem S. Hara, Danae Pla Karidi, Ester Zumpano, Fabio Persia, Genoveva Vargas-Solar, George Papastefanatos, Giancarlo Sperlì, Giorgos Giannopoulos, Ivan Lukovic, Julien Aligon, Manolis Terrovitis, Marek Grzegorowski, Mariella Bonomo, Mirian Halfeld Ferrari Alves, Nicolas Labroche, Paul Monsarrat, Richard Chbeir, Sana Sellami, Seshu Tirupathi, Simona E. Rombo, Slavica Kordic, Sonja Ristic, Tommaso Di Noia, Torben Bach Pedersen, Vincenzo Moscato
2023	J	`jnl`	Explanations as a New Metric for Feature Selection: A Systematic Approach. IEEE J. Biomed. Health Informatics Haomiao Wang, Emmanuel Doumard, Chantal Soulé-Dupuy, Philippe Kémoun, Julien Aligon, Paul Monsarrat
2023	C	`conf`	How to Make the Most of Local Explanations: Effective Clustering Based on Influences. ADBIS Elodie Escriva, Julien Aligon, Jean-Baptiste Excoffier, Paul Monsarrat, Chantal Soulé-Dupuy
2022	C	`conf`	A Comparative Study of Additive Local Explanation Methods based on Feature Influences. DOLAP Emmanuel Doumard, Julien Aligon, Elodie Escriva, Jean-Baptiste Excoffier, Paul Monsarrat, Chantal Soulé-Dupuy
2019	J	`jnl`	The progressive substitution of hazard ratios for relative risks in biomedical research. Scientometrics Paul Monsarrat, Jean-Noel Vergnes
2018	J	`jnl`	Data mining of effect sizes from PubMed abstracts: a cross-study conceptual replication. Bioinform. Paul Monsarrat, Jean-Noel Vergnes

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.