Zhangchun Tang

14 papers Journal 10Unranked 4

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Interaction effects of multiple input parameters on the integrity of safety instrumented systems with the k-out-of-n redundancy arrangement under uncertainties. Qual. Reliab. Eng. Int. Yanjun Xia, Linfei Ding, Zhangchun Tang
2023	—	`conf`	Natural Language Processing Combined with Digital Twins to Drive Fusion Physics Design. AIBDF Zilong Yuan, Pan Liu, Huan Mao, Gaoyang Liu, Wenbin Xiong, Zhangchun Tang
2022	—	`conf`	Physical design for driven device of Z-FFR based on Machine Learning. ISCID Wenbin Xiong, Zhangchun Tang, Pan Liu, Gaoyang Liu, Fanyu Qu, Qiang Gao, Chencheng Liu
2022	—	`conf`	Physical design of fusion based on generative adversarial networks. ACAI Wenbin Xiong, Pan Liu, Zhangchun Tang, Yan Shi, Chencheng Liu, Fanyu Qu, Gaoyang Liu, Qiang Gao
2022	—	`conf`	Research on Fault Diagnosis of Nuclear Gate Valve Based on Analysis of Energy Variation Characteristics of Vibration Signal. ICPHM Zhilong Liu, Tongxi Li, Yanping Huang, Jie Liu, Changhua Nie, Li Zhan, Zhangchun Tang
2018	J	`jnl`	A surrogate-based iterative importance sampling method for structural reliability analysis. Qual. Reliab. Eng. Int. Zhangchun Tang, Yanjun Xia
2017	J	`jnl`	Effect of Truncated Input Parameter Distribution on the Integrity of Safety Instrumented Systems Under Epistemic Uncertainty. IEEE Trans. Reliab. Zhangchun Tang, Ming Jian Zuo, Yanjun Xia
2016	J	`jnl`	An efficient method for evaluating the effect of input parameters on the integrity of safety systems. Reliab. Eng. Syst. Saf. Zhangchun Tang, Ming Jian Zuo, Ning-Cong Xiao
2015	J	`jnl`	Multi-Sensor Data Fusion Using a Relevance Vector Machine Based on an Ant Colony for Gearbox Fault Detection. Sensors Zhiwen Liu, Wei Guo, Zhangchun Tang, Yongqiang Chen
2014	J	`jnl`	An efficient approach for design optimization of structures involving fuzzy variables. Fuzzy Sets Syst. Zhangchun Tang, Zhenzhou Lu, Jixiang Hu
2014	J	`jnl`	Reliability-Based Design Optimization for the Structures with Fuzzy Variables and Uncertain-but-Bounded Variables. J. Aerosp. Inf. Syst. Zhangchun Tang, Zhenzhou Lu
2013	J	`jnl`	A derivative based sensitivity measure of failure probability in the presence of epistemic and aleatory uncertainties. Comput. Math. Appl. Pan Wang, Zhenzhou Lu, Zhangchun Tang
2013	J	`jnl`	A mean extrapolation technique for high reliability analysis. Appl. Math. Comput. Zhangchun Tang, Zhenzhou Lu, Pan Wang, Zhang Feng
2013	J	`jnl`	Importance measure analysis with epistemic uncertainty and its moving least squares solution. Comput. Math. Appl. Pan Wang, Zhenzhou Lu, Zhangchun Tang

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.