Abubakar Siddique

16 papers A 1B 2Misc 1Journal 5Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Lateralized Learning for Multi-Class Visual Classification Tasks. IEEE Access Abubakar Siddique, Will N. Browne, Gina M. Grimshaw
2025	—	`conf`	Evolving Modular Abstractions through Lateralized Learning in Classifier Systems. GECCO Companion Abubakar Siddique, Muhammad Iqbal, Will N. Browne, Gina M. Grimshaw
2024	—	`conf`	A Survey on Learning Classifier Systems from 2022 to 2024. GECCO Companion Abubakar Siddique, Michael Heider, Muhammad Iqbal, Hiroki Shiraishi
2024	Misc	`conf`	Enhancing Visual Focus: Incorporating Attention into Rule-Based Machine Learning. IVCNZ Abubakar Siddique, Muhammad Iqbal, Will N. Browne
2024	—	`conf`	Evolutionary Machine Learning for Interpretable and eXplainable AI. GECCO Companion Abubakar Siddique, Will N. Browne, Ryan J. Urbanowicz
2023	—	`conf`	Attention in Rule-Based Machine Learning: Exploiting Learning Classifier Systems' Generalization for Image Classification. GECCO Companion Abubakar Siddique, Muhammad Iqbal, Shahab Ud Din, Will N. Browne
2023	J	`jnl`	Lateralization in Agents' Decision Making: Evidence of Benefits/Costs from Artificial Intelligence. CoRR Abubakar Siddique, Will N. Browne, Gina M. Grimshaw
2023	J	`jnl`	Lateralized Learning for Multi-Class Visual Classification Tasks. CoRR Abubakar Siddique, Will N. Browne, Gina M. Grimshaw
2023	J	`jnl`	Lateralized Learning to Solve Complex Boolean Problems. IEEE Trans. Cybern. Abubakar Siddique, Will N. Browne, Gina M. Grimshaw
2023	—	`conf`	Modern Applications of Evolutionary Rule-based Machine Learning. GECCO Companion Abubakar Siddique, Will N. Browne, Ryan J. Urbanowicz
2022	J	`jnl`	Frames-of-Reference-Based Learning: Overcoming Perceptual Aliasing in Multistep Decision-Making Tasks. IEEE Trans. Evol. Comput. Abubakar Siddique, Will N. Browne, Gina M. Grimshaw
2022	—	`conf`	Learning classifier systems: cognitive inspired machine learning for eXplainable AI. GECCO Companion Abubakar Siddique, Will N. Browne
2021	B	`conf`	Lateralized Approach for Robustness Against Attacks in Emotion Categorization from Images. EvoApplications Harisu Abdullahi Shehu, Abubakar Siddique, Will N. Browne, Hedwig Eisenbarth
2020	A	`conf`	Lateralized learning for robustness against adversarial attacks in a visual classification system. GECCO Abubakar Siddique, Will N. Browne, Gina M. Grimshaw
2020	—	`conf`	Learning classifier systems: appreciating the lateralized approach. GECCO Companion Abubakar Siddique, Will N. Browne, Gina M. Grimshaw
2016	B	`conf`	A comprehensive strategy for mammogram image classification using learning classifier systems. CEC Abubakar Siddique, Muhammad Iqbal, Will N. Browne

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.