Yang Liu - RankMe

21 papers Journal 21

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Biologically inspired energy-balanced clustering routing optimization for wireless sensor networks. Expert Syst. Appl. Mengying Xu, Yunxiao Zu, Jie Zhou, Yang Liu, Chaoqun Li
2025	J	`jnl`	Efficient Maximum Proc. ACM Manag. Data Yang Liu, Hejiao Huang, Kaiqiang Yu, Shengxin Liu, Cheng Long
2025	J	`jnl`	Efficient Size-Bounded Community Search, Revisited: Frameworks for Practical Improvements. Proc. ACM Manag. Data Yang Liu, Hejiao Huang, Kaiqiang Yu, Shengxin Liu, Cheng Long, Zhaoquan Gu
2025	J	`jnl`	Minimum $k$k-Vertex Connected Graph Search. IEEE Trans. Knowl. Data Eng. Yang Liu, Hejiao Huang, Kaiqiang Yu, Shengxin Liu, Cheng Long
2024	J	`jnl`	A Dual Cluster Head Hierarchical Routing Protocol for Wireless Sensor Networks Based on Hybrid Swarm Intelligence Optimization. IEEE Internet Things J. Yang Liu, Hejiao Huang, Jie Zhou
2024	J	`jnl`	An Innovative Cluster Routing Method for Performance Enhancement in Underwater Acoustic Sensor Networks. IEEE Internet Things J. Tao Luo, Baitao Zhang, Jiahao Li, Jing Xiao, Chaoqun Li, Yang Liu, Yao Zhang, Jie Zhou
2024	J	`jnl`	Energy-Efficient Secure QoS Routing Algorithm Based on Elite Niche Clone Evolutionary Computing for WSN. IEEE Internet Things J. Mengying Xu, Yunxiao Zu, Jie Zhou, Yang Liu, Chaoqun Li
2023	J	`jnl`	A Novel Nature-Inspired Routing Scheme for Improving Routing Quality of Service in Power Grid Monitoring Systems. IEEE Syst. J. Chaoqun Li, Yang Liu, Yao Zhang, Mengying Xu, Jing Xiao, Jie Zhou
2023	J	`jnl`	DCC-IACJS: A novel bio-inspired duty cycle-based clustering approach for energy-efficient wireless sensor networks. J. King Saud Univ. Comput. Inf. Sci. Yang Liu, Chaoqun Li, Yao Zhang, Mengying Xu, Jing Xiao, Jie Zhou
2022	J	`jnl`	A Novel Niche Quantum Ant Colony-Based Clustering Optimization Approach for Wireless Auto Meter Reading Network. J. Sensors Jingyun Li, Hu Qin, Yang Liu, Jie Zhou, Yao Zhang
2022	J	`jnl`	A novel multi-level population hybrid search evolution algorithm for constrained multi-objective optimization problems. J. King Saud Univ. Comput. Inf. Sci. Chaoqun Li, Yang Liu, Yao Zhang, Mengying Xu, Jing Xiao, Jie Zhou
2022	J	`jnl`	An immune chaotic adaptive evolutionary algorithm for energy-efficient clustering management in LPWSN. J. King Saud Univ. Comput. Inf. Sci. Yao Zhang, Jianpeng Xie, Yang Liu, Chaoqun Li, Jing Xiao, Hongliang Ma, Jie Zhou
2022	J	`jnl`	HPCP-QCWOA: High Performance Clustering Protocol based on Quantum Clone Whale Optimization Algorithm in Integrated Energy System. Future Gener. Comput. Syst. Yang Liu, Chaoqun Li, Yao Zhang, Mengying Xu, Jing Xiao, Jie Zhou
2022	J	`jnl`	MCEAACO-QSRP: A Novel QoS-Secure Routing Protocol for Industrial Internet of Things. IEEE Internet Things J. Chaoqun Li, Yang Liu, Jing Xiao, Jie Zhou
2022	J	`jnl`	QEGWO: Energy-Efficient Clustering Approach for Industrial Wireless Sensor Networks Using Quantum-Related Bioinspired Optimization. IEEE Internet Things J. Yang Liu, Chaoqun Li, Jing Xiao, Zhigang Li, Wenbin Chen, Xin Qu, Jie Zhou
2021	J	`jnl`	A Novel QoS Routing Energy Consumption Optimization Method Based on Clone Adaptive Whale Optimization Algorithm in IWSNs. J. Sensors Jing Xiao, Yang Liu, Hu Qin, Chaoqun Li, Jie Zhou
2021	J	`jnl`	An Adaptive Immune Ant Colony Optimization for Reducing Energy Consumption of Automatic Inspection Path Planning in Industrial Wireless Sensor Networks. J. Sensors Chaoqun Li, Jing Xiao, Yang Liu, Guohong Qi, Hu Qin, Jie Zhou
2021	J	`jnl`	An Improved Adaptive Clone Genetic Algorithm for Task Allocation Optimization in ITWSNs. J. Sensors Zhihua Zha, Chaoqun Li, Jing Xiao, Yao Zhang, Hu Qin, Yang Liu, Jie Zhou, Jie Wu
2021	J	`jnl`	Hybrid Niche Immune Genetic Algorithm for Fault Detection Coverage in Industry Wireless Sensor Network. J. Sensors Jie Zhou, Hu Qin, Yang Liu, Chaoqun Li, Mengying Xu
2021	J	`jnl`	Quantum Clone Elite Genetic Algorithm-Based Evaluation Mechanism for Maximizing Network Efficiency in Soil Moisture Wireless Sensor Networks. J. Sensors Jing Xiao, Yang Liu, Jie Zhou
2021	J	`jnl`	Sensor Duty Cycle for Prolonging Network Lifetime Using Quantum Clone Grey Wolf Optimization Algorithm in Industrial Wireless Sensor Networks. J. Sensors Yang Liu, Jing Xiao, Chaoqun Li, Hu Qin, Jie Zhou

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.