Leo A. M. van Dongen

14 papers Journal 8Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Using Functional Blocks for Rolling Stock Troubleshooting: Sequential Augmented Reality Assistant (SARA). IEEE Access Sara Scheffer, Alberto Martinetti, Roy G. J. Damgrave, Leo A. M. van Dongen
2023	J	`jnl`	Ready, trainer ... one*! discovering the entanglement of adaptive learning with virtual reality in industrial training: a case study. Interact. Learn. Environ. Yawar Abbas, Alberto Martinetti, Kostas Nizamis, Steven Spoolder, Leo A. M. van Dongen
2022	J	`jnl`	Graceful extensibility in asset management: extending the capacity to adapt in managing cyber-physical railway systems. Cogn. Technol. Work. Jan-Jaap Moerman, Jan Maarten Schraagen, Jan Braaksma, Leo A. M. van Dongen
2022	J	`jnl`	Investigating Interdependencies Between Key Features of Lessons Learned: An Integral Approach for Knowledge Sharing. J. Inf. Knowl. Manag. Yawar Abbas, Alberto Martinetti, Lex Frunt, Jeroen Klinkers, Mohammad Rajabalinejad, Leo A. M. van Dongen
2020	—	`conf`	A Multi-domain Approach Toward Adaptations of Socio-technical Systems: The Dutch Railway Case-Part 1. SoSE Mohsen Jafari Songhori, Leo A. M. van Dongen, Mohammad Rajabalinejad
2020	—	`conf`	A Multi-domain Approach Toward Adaptations of Socio-technical Systems: The Dutch Railway Case-Part 2. SoSE Mohsen Jafari Songhori, Leo A. M. van Dongen, Mohammad Rajabalinejad
2020	J	`jnl`	Do you have confidence in how your rolling stock has been maintained? A blockchain-led knowledge-sharing platform for building trust between stakeholders. Int. J. Inf. Manag. Yawar Abbas, Alberto Martinetti, Jan-Jaap Moerman, Ton Hamberg, Leo A. M. van Dongen
2020	—	`conf`	Reflections on the Adoption of Virtual Adaptive Learning Tool for Industrial Training. IHIET (Lausanne) Alberto Martinetti, Micaela Demichela, Steven Spoolder, Joep von Berg, Leo A. M. van Dongen
2020	—	`conf`	The System (of Interest) Definitions phase: Key features and challenges in the Dutch Railway system. SoSE Merishna Ramtahalsing, Mohsen Jafari, Jan Braaksma, Mohammad Rajabalinejad, Leo A. M. van Dongen
2019	—	`conf`	Collaborative Decision-Making Challenges in the Dutch Railway System. CSDM Nina Jakubeit, Mohammad Rajabalinejad, Jan Braaksma, Leo A. M. van Dongen
2018	J	`jnl`	Framing success: the Netherlands railways experience. Int. J. Syst. Syst. Eng. Mohammad Rajabalinejad, Leo A. M. van Dongen
2018	J	`jnl`	There is no spoon: applying virtual reality for maintenance training of rolling stock technicians. Int. J. Syst. Syst. Eng. Alberto Martinetti, K. 't Hart, Roy G. J. Damgrave, Leo A. M. van Dongen, R. Turkenburg, Andre Nouwens
2018	J	`jnl`	Wheel maintenance in rolling stock: safety challenges in the defect detection process. Int. J. Syst. Syst. Eng. Maria Mikela Chatzimichailidou, Alberto Martinetti, Arnab Majumdar, Leo A. M. van Dongen, Washington Yotto Ochieng
2016	—	`conf`	Operation, safety and human: Critical factors for the success of railway transportation. SoSE Mohammad Rajabalinejad, Alberto Martinetti, Leo A. M. van Dongen

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.