Zenghong Huang

15 papers Journal 14Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Distributed Receding Horizon Estimation for Time Invariant Discrete Time Linear Systems Based on Substate Decomposition. IEEE Trans. Netw. Sci. Eng. Zenghong Huang, Zijie Chen, Yong Xu, Chang Liu, Peng Shi
2026	J	`jnl`	Distributed Set-Membership Filtering Over Wireless Sensor Networks With Coding-Decoding Mechanism. IEEE Trans. Circuits Syst. I Regul. Pap. Tianyang Zhang, Zenghong Huang, Chang Liu, Jun-Yi Li, Yong Xu, Tingwen Huang
2025	J	`jnl`	Distributed Set-Membership Filtering for Sensor Networks: An Event-Triggered Approach. IEEE Trans. Ind. Informatics Tianyang Zhang, Zenghong Huang, Chang Liu, Yong Xu, Tingwen Huang
2024	J	`jnl`	Event-Triggered Distributed Moving Horizon Estimation Over Wireless Sensor Networks. IEEE Trans. Ind. Informatics Zenghong Huang, Weijun Lv, Chang Liu, Yong Xu, Leszek Rutkowski, Tingwen Huang
2024	J	`jnl`	Hybrid Transmission Scheduling Protocol for State Estimation Over a Constrained Channel. IEEE Trans. Control. Netw. Syst. Weijun Lv, Yong Xu, Zenghong Huang, Hongxia Rao, Ling Shi
2023	J	`jnl`	Consensus-based distributed moving horizon estimation with constraints. Inf. Sci. Zenghong Huang, Zijie Chen, Chang Liu, Yong Xu, Peng Shi
2023	J	`jnl`	Distributed Estimation and Smoothing for Linear Dynamic Systems Over Sensor Networks. IEEE Trans. Circuits Syst. I Regul. Pap. Yunsong Deng, Zenghong Huang, Yijin Jia, Yong Xu, Peng Shi
2023	J	`jnl`	Distributed Moving Horizon Estimation Over Wireless Sensor Networks: A Matrix-Weighted Consensus Approach. IEEE Trans. Circuits Syst. II Express Briefs Zenghong Huang, Yuru Guo, Hui Peng, Yong Xu
2023	J	`jnl`	Distributed State Estimation Over Sensor Networks With Substate Decomposition Approach. IEEE Trans. Netw. Sci. Eng. Yong Xu, Yunsong Deng, Zenghong Huang, Ming Lin, Peng Shi
2023	J	`jnl`	Learning Optimal Stochastic Sensor Scheduling for Remote Estimation With Channel Capacity Constraint. IEEE Trans. Ind. Informatics Lixin Yang, Yong Xu, Zenghong Huang, Hong-Xia Rao, Daniel E. Quevedo
2023	J	`jnl`	Pinning synchronization for markovian jump neural networks with uncertain impulsive effects. Neurocomputing Yuru Guo, Zenghong Huang, Lixin Yang, Hong-Xia Rao, Hui Chen, Yong Xu
2022	J	`jnl`	Distributed Newton Optimization With Maximized Convergence Rate. IEEE Trans. Autom. Control. Damián Marelli, Yong Xu, Minyue Fu, Zenghong Huang
2022	J	`jnl`	Quasisynchronization for Neural Networks With Partial Constrained State Information via Intermittent Control Approach. IEEE Trans. Cybern. Hong-Xia Rao, Liwei Zhao, Yong Xu, Zenghong Huang, Renquan Lu
2021	J	`jnl`	Lag quasi-synchronization for periodic neural networks with unreliable redundant communication channels. Neurocomputing Hong-Xia Rao, Hui Chen, Zebing Huang, Zenghong Huang, Yuru Guo
2021	—	`conf`	State Estimation for Discrete Time Linear Systems with Nonlinear measurements and Round-Robin Protocol. SPAC Zitian Li, Zenghong Huang, Lixin Yang, Jie Li, Hong-Xia Rao

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.