Qianwei Zhang

11 papers Journal 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Untrained neural networks in data-scarce smart manufacturing: a paradigm for data-efficient industrial intelligence. Comput. Ind. Eng. Jiewu Leng, Jiahe Li, Qianwei Zhang, Xuyang Su, Bo Yang, Liang Guo, Qiang Liu, Xin Chen, Weiming Shen, Lihui Wang
2025	J	`jnl`	Q-learning driven cooperative evolution with dual-reputation incentive mechanisms. Appl. Math. Comput. Qianwei Zhang, Xinran Zhang
2024	J	`jnl`	Common revenue allocation in DMUs with two stages based on DEA cross-efficiency and cooperative game. CoRR Xinyu Wang, Qianwei Zhang, Yilun Lu, Yingdi Zhao
2024	J	`jnl`	The common revenue allocation based on modified Shapley value and DEA cross-efficiency. CoRR Xinyu Wang, Qianwei Zhang, Binwei Gui, Yingdi Zhao
2024	J	`jnl`	The impact of anxiety on cooperative behavior: A network evolutionary game theory approach. Appl. Math. Comput. Qianwei Zhang, Rui Tang, Yilun Lu, Xinyu Wang
2023	J	`jnl`	Investigating relationships among regulated learning, teaching presence and student engagement in blended learning: An experience sampling analysis. Educ. Inf. Technol. Hongjian Liao, Qianwei Zhang, Lin Yang, Yuenong Fei
2022	J	`jnl`	Optimization of Cockpit Ventilation for Polar Cruise Ships in Combination with Windscreen Defogging and Cabin Comfort Considerations. Entropy Hong Shi, Qianwei Zhang, Wenbing Xu, Meinan Liu, Jiashuang Pan, Jie Yuan, Kaijie Yang
2021	J	`jnl`	Development of a Mobile Platform for Field-Based High-Throughput Wheat Phenotyping. Remote. Sens. Majid Khak Pour, Reza Fotouhi, Pierre Hucl, Qianwei Zhang
2017	J	`jnl`	Coalitional game with fuzzy payoffs and credibilistic nucleolus. J. Intell. Fuzzy Syst. Qianwei Zhang, Zhihua Yang, Binwei Gui
2015	J	`jnl`	Resource allocation based on DEA and modified Shapley value. Appl. Math. Comput. Zhihua Yang, Qianwei Zhang
2015	J	`jnl`	Returns to scale of two-stage production process. Comput. Ind. Eng. Qianwei Zhang, Zhihua Yang

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.