L. Andrew Coward

15 papers B 3Misc 1Journal 8Unranked 3

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Hierarchies of description enable understanding of cognitive phenomena in terms of neuron activity. Cogn. Process. L. Andrew Coward
2023	J	`jnl`	Leveraging conscious and nonconscious learning for efficient AI. Frontiers Comput. Neurosci. Rachel St. Clair, L. Andrew Coward, Susan Schneider
2016	J	`jnl`	Using the Change Manager Model for the Hippocampal System to Predict Connectivity and Neurophysiological Parameters in the Perirhinal Cortex. Comput. Intell. Neurosci. L. Andrew Coward, Tom Gedeon
2014	—	`conf`	Brain Computational Primitives. BICA L. Andrew Coward
2011	—	`conf`	Architectures of Complex Learning Systems. BICA L. Andrew Coward, Tamas O. Gedeon
2011	—	`conf`	Brain Anatomy and Artificial Intelligence. AGI L. Andrew Coward
2009	J	`jnl`	Implications of resource limitations for a conscious machine. Neurocomputing L. Andrew Coward, Tamas O. Gedeon
2007	J	`jnl`	Hierarchical approaches to understanding consciousness. Neural Networks L. Andrew Coward, Ron Sun
2006	B	`conf`	Constraints on the Design Process for Systems with Human Level Intelligence. IJCNN L. Andrew Coward
2004	B	`conf`	Learning complex combinations of operations in a hybrid architecture. FUZZ-IEEE L. Andrew Coward, Tamás D. Gedeon, Uditha Ratnayake
2004	B	`conf`	Managing Interference Between Prior and Later Learning. ICONIP L. Andrew Coward, Tamás D. Gedeon, Uditha Ratnayake
2004	J	`jnl`	The Information Architecture of Cities. J. Inf. Sci. L. Andrew Coward, Nikos A. Salingaros
2001	J	`jnl`	Application of the Recommendation Architecture to Telecommunications Network Management. Int. J. Neural Syst. L. Andrew Coward, Tom Gedeon, William Kenworthy
2001	J	`jnl`	The recommendation architecture: lessons from large-scale electronic systems applied to cognition. Cogn. Syst. Res. L. Andrew Coward
1997	Misc	`conf`	The Pattern Extraction Architecture: A Connectionist Alternative to the Von Neumann Architecture. IWANN L. Andrew Coward

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.

In 2025, he co-authored Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja, published at CheckMATE. The paper evaluates the effectiveness of obfuscation techniques and their impact on source-level static analysis and binary-level decompilation.

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.