Fabrizio Russo

18 papers A* 5A 1Journal 9Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Heterogeneous Graph Neural Networks for Assumption-Based Argumentation. AAAI Preesha Gehlot, Anna Rapberger, Fabrizio Russo, Francesca Toni
2026	J	`jnl`	Leveraging Large Language Models for Causal Discovery: a Constraint-based, Argumentation-driven Approach. CoRR Zihao Li, Fabrizio Russo
2025	J	`jnl`	Heterogeneous Graph Neural Networks for Assumption-Based Argumentation. CoRR Preesha Gehlot, Anna Rapberger, Fabrizio Russo, Francesca Toni
2025	—	`conf`	Heterogeneous Graph Neural Networks for Credulous Acceptance of Assumptions in ABA. Arg&App 2025 Preesha Gehlot, Anna Rapberger, Fabrizio Russo, Francesca Toni
2025	A*	`conf`	On Gradual Semantics for Assumption-Based Argumentation. KR Anna Rapberger, Fabrizio Russo, Antonio Rago, Francesca Toni
2025	J	`jnl`	On Gradual Semantics for Assumption-Based Argumentation. CoRR Anna Rapberger, Fabrizio Russo, Antonio Rago, Francesca Toni
2025	—	`conf`	Shapley-PC: Constraint-based Causal Structure Learning with a Shapley Inspired Framework. CLeaR Fabrizio Russo, Francesca Toni
2024	A*	`conf`	Argumentative Causal Discovery. KR Fabrizio Russo, Anna Rapberger, Francesca Toni
2024	J	`jnl`	Argumentative Causal Discovery. CoRR Fabrizio Russo, Anna Rapberger, Francesca Toni
2024	A*	`conf`	Contestable AI Needs Computational Argumentation. KR Francesco Leofante, Hamed Ayoobi, Adam Dejl, Gabriel Freedman, Deniz Gorur, Junqi Jiang, Guilherme Paulino-Passos, Antonio Rago, Anna Rapberger, Fabrizio Russo, Xiang Yin, Dekai Zhang, Francesca Toni
2024	J	`jnl`	Contestable AI needs Computational Argumentation. CoRR Francesco Leofante, Hamed Ayoobi, Adam Dejl, Gabriel Freedman, Deniz Gorur, Junqi Jiang, Guilherme Paulino-Passos, Antonio Rago, Anna Rapberger, Fabrizio Russo, Xiang Yin, Dekai Zhang, Francesca Toni
2024	J	`jnl`	Online Handbook of Argumentation for AI: Volume 4. CoRR Lars Bengel, Lydia Blümel, Elfia Bezou-Vrakatseli, Federico Castagna, Giulia D'Agostino, Isabelle Kuhlmann, Jack Mumford, Daphne Odekerken, Fabrizio Russo, Stefan Sarkadi, Madeleine Waller, Andreas Xydis
2023	A*	`conf`	Argumentation for Interactive Causal Discovery. IJCAI Fabrizio Russo
2023	A	`conf`	Causal Discovery and Knowledge Injection for Contestable Neural Networks. ECAI Fabrizio Russo, Francesca Toni
2023	J	`jnl`	Explaining Classifiers' Outputs with Causal Models and Argumentation. FLAP Antonio Rago, Fabrizio Russo, Emanuele Albini, Francesca Toni, Pietro Baroni
2023	J	`jnl`	Shapley-PC: Constraint-based Causal Structure Learning with Shapley Values. CoRR Fabrizio Russo, Francesca Toni
2022	J	`jnl`	Causal Discovery and Injection for Feed-Forward Neural Networks. CoRR Fabrizio Russo, Francesca Toni
2021	—	`conf`	Forging Argumentative Explanations from Causal Models. AI³@AI*IA Antonio Rago, Fabrizio Russo, Emanuele Albini, Pietro Baroni, Francesca Toni

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.