Emanuele Albini

20 papers A* 2A 1C 3Journal 9Unranked 5

Year	Rank	Type	Title / Venue / Authors
2024	—	`conf`	PICE: Polyhedral Complex Informed Counterfactual Explanations. AIES (1) Mattia Jacopo Villani, Emanuele Albini, Shubham Sharma, Saumitra Mishra, Salim Ibrahim Amoukou, Daniele Magazzeni, Manuela Veloso
2024	J	`jnl`	REFRESH: Responsible and Efficient Feature Reselection Guided by SHAP Values. CoRR Shubham Sharma, Sanghamitra Dutta, Emanuele Albini, Freddy Lécué, Daniele Magazzeni, Manuela Veloso
2023	J	`jnl`	Achieving descriptive accuracy in explanations via argumentation: The case of probabilistic classifiers. Frontiers Artif. Intell. Emanuele Albini, Antonio Rago, Pietro Baroni, 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	C	`conf`	On the Connection between Game-Theoretic Feature Attributions and Counterfactual Explanations. AIES Emanuele Albini, Shubham Sharma, Saumitra Mishra, Danial Dervovic, Daniele Magazzeni
2023	J	`jnl`	On the Connection between Game-Theoretic Feature Attributions and Counterfactual Explanations. CoRR Emanuele Albini, Shubham Sharma, Saumitra Mishra, Danial Dervovic, Daniele Magazzeni
2023	C	`conf`	REFRESH: Responsible and Efficient Feature Reselection guided by SHAP values. AIES Shubham Sharma, Sanghamitra Dutta, Emanuele Albini, Freddy Lécué, Daniele Magazzeni, Manuela Veloso
2022	—	`conf`	Counterfactual Shapley Additive Explanations. FAccT Emanuele Albini, Jason Long, Danial Dervovic, Daniele Magazzeni
2022	—	`conf`	Descriptive Accuracy in Explanations: The Case of Probabilistic Classifiers. SUM Emanuele Albini, Antonio Rago, Pietro Baroni, Francesca Toni
2021	A	`conf`	Argflow: A Toolkit for Deep Argumentative Explanations for Neural Networks. AAMAS Adam Dejl, Chloe He, Pranav Mangal, Hasan Mohsin, Bogdan Surdu, Eduard Voinea, Emanuele Albini, Piyawat Lertvittayakumjorn, Antonio Rago, Francesca Toni
2021	A*	`conf`	Argumentative XAI: A Survey. IJCAI Kristijonas Cyras, Antonio Rago, Emanuele Albini, Pietro Baroni, Francesca Toni
2021	J	`jnl`	Argumentative XAI: A Survey. CoRR Kristijonas Cyras, Antonio Rago, Emanuele Albini, Pietro Baroni, Francesca Toni
2021	J	`jnl`	Counterfactual Shapley Additive Explanations. CoRR Emanuele Albini, Jason Long, Danial Dervovic, Daniele Magazzeni
2021	—	`conf`	Forging Argumentative Explanations from Causal Models. AI³@AI*IA Antonio Rago, Fabrizio Russo, Emanuele Albini, Pietro Baroni, Francesca Toni
2021	—	`conf`	Influence-Driven Explanations for Bayesian Network Classifiers. PRICAI (1) Emanuele Albini, Antonio Rago, Pietro Baroni, Francesca Toni
2021	J	`jnl`	Interpreting and explaining pagerank through argumentation semantics. Intelligenza Artificiale Emanuele Albini, Pietro Baroni, Antonio Rago, Francesca Toni
2020	J	`jnl`	DAX: Deep Argumentative eXplanation for Neural Networks. CoRR Emanuele Albini, Piyawat Lertvittayakumjorn, Antonio Rago, Francesca Toni
2020	J	`jnl`	Influence-Driven Explanations for Bayesian Network Classifiers. CoRR Antonio Rago, Emanuele Albini, Pietro Baroni, Francesca Toni
2020	C	`conf`	PageRank as an Argumentation Semantics. COMMA Emanuele Albini, Pietro Baroni, Antonio Rago, Francesca Toni
2020	A*	`conf`	Relation-Based Counterfactual Explanations for Bayesian Network Classifiers. IJCAI Emanuele Albini, Antonio Rago, 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.