Yanjun Chen - RankMe

13 papers Journal 12Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Hierarchical fault diagnosis of train communication networks based on cross-dimensional information fusion and mixture-of-head attention mechanism. Reliab. Eng. Syst. Saf. Deqiang He, Mi Liang, Jinxin Wu, Zhenzhen Jin, Yanjun Chen
2024	J	`jnl`	Few-shot fault diagnosis of switch machine based on data fusion and balanced regularized prototypical network. Eng. Appl. Artif. Intell. Zhenpeng Lao, Deqiang He, Haimeng Sun, Yiling He, Zhiping Lai, Sheng Shan, Yanjun Chen
2024	J	`jnl`	Few-shot fault diagnosis of turnout switch machine based on flexible semi-supervised meta-learning network. Knowl. Based Syst. Yiling He, Deqiang He, Zhenpeng Lao, Zhenzhen Jin, Jian Miao, Zhiping Lai, Yanjun Chen
2024	J	`jnl`	Research on flow scheduling of train communication based on time-sensitive network. Simul. Model. Pract. Theory Tiexiang Liu, Deqiang He, Zhenzhen Jin, Sheng Shan, Yanjun Chen, Qilin Chen
2024	J	`jnl`	Welding defect detection based on phased array images and two-stage segmentation strategy. Adv. Eng. Informatics Yan Chen, Deqiang He, Suiqiu He, Zhenzhen Jin, Jian Miao, Sheng Shan, Yanjun Chen
2023	J	`jnl`	Density-Based Affinity Propagation Tensor Clustering for Intelligent Fault Diagnosis of Train Bogie Bearing. IEEE Trans. Intell. Transp. Syst. Zexian Wei, Deqiang He, Zhenzhen Jin, Bin Liu, Sheng Shan, Yanjun Chen, Jian Miao
2022	J	`jnl`	Evaluation and Prediction of Train Communication Network Performance. IEEE Trans. Veh. Technol. Deqiang He, Guoqiang Liu, Yanjun Chen, Jian Miao, Xiaoyang Yao
2022	J	`jnl`	Fault diagnosis of train rotating parts based on multi-objective VMD optimization and ensemble learning. Digit. Signal Process. Zhenzhen Jin, Deqiang He, Rui Ma, Xueyan Zou, Yanjun Chen, Sheng Shan
2022	J	`jnl`	Topology Design and Optimization of Train Communication Network Based on Industrial Ethernet. IEEE Trans. Veh. Technol. Deqiang He, Daliang Sun, Yanjun Chen, Guoqiang Liu, Songlin Guo, Rui Ma, Jian Miao, Jianren Liu
2021	J	`jnl`	Rail Transit Obstacle Detection Based on Improved CNN. IEEE Trans. Instrum. Meas. Deqiang He, Zhiheng Zou, Yanjun Chen, Bin Liu, Jian Miao
2020	—	`conf`	Topology Optimization of Train Communication Network Based on Improved Adaptive Genetic Algorithm. ICCT Deqiang He, Yasong Wang, Yanjun Chen, Yuzhao Yuan, Tao Chen, Jianren Liu
2019	J	`jnl`	Detection of Foreign Matter on High-Speed Train Underbody Based on Deep Learning. IEEE Access Deqiang He, Zikai Yao, Zhou Jiang, Yanjun Chen, Jianxin Deng, Weibin Xiang
2019	J	`jnl`	Optimal Control of Metro Energy Conservation Based on Regenerative Braking: A Complex Model Study of Trajectory and Overlap Time. IEEE Access Deqiang He, Yanjie Yang, Jixu Zhou, Yanjun Chen

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.