Tao Yang

16 papers C 1Journal 14Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A deep autoencoder with structured latent space for process monitoring and anomaly detection in coal-fired power units. Reliab. Eng. Syst. Saf. Di Hu, Chen Zhang, Tao Yang, Qingyan Fang
2025	J	`jnl`	Threshold-Varying Assessment for Prognostics and Health Management. IEEE Trans. Syst. Man Cybern. Syst. Dongzhen Lyu, Enhui Liu, Bin Zhang, Enrico Zio, Tao Yang, Jiawei Xiang
2024	J	`jnl`	Research of artificial intelligence operations for wind turbines considering anomaly detection, root cause analysis, and incremental training. Reliab. Eng. Syst. Saf. Chen Zhang, Di Hu, Tao Yang
2023	J	`jnl`	Low-Cost Adaptive LS-DEKF for SOC Estimation and RDT Prediction With SFP Model. IEEE Trans. Instrum. Meas. Enhui Liu, Guangxing Niu, Dongzhen Lyu, Tao Yang, Bin Zhang
2022	J	`jnl`	Anomaly detection and diagnosis for wind turbines using long short-term memory-based stacked denoising autoencoders and XGBoost. Reliab. Eng. Syst. Saf. Chen Zhang, Di Hu, Tao Yang
2022	J	`jnl`	Image Recognition of Wind Turbine Blade Defects Using Attention-Based MobileNetv1-YOLOv4 and Transfer Learning. Sensors Chen Zhang, Tao Yang, Jing Yang
2022	J	`jnl`	Lebesgue Sampling-Based Li-Ion Battery Simplified First Principle Model for SOC Estimation and RDT Prediction. IEEE Trans. Ind. Electron. Enhui Liu, Xuan Wang, Guangxing Niu, Dongzhen Lyu, Tao Yang, Bin Zhang
2022	C	`conf`	The explainable uncertainty in degradation process: a discovery from non-accelerated batteries degradation experiment. IECON Dongzhen Lyu, Bin Zhang, Enrico Zio, Tao Yang
2022	J	`jnl`	Time space modelling for fault diagnosis and prognosis with uncertainty management: A general theoretical formulation. Reliab. Eng. Syst. Saf. Dongzhen Lyu, Guangxing Niu, Enhui Liu, Bin Zhang, Gang Chen, Tao Yang, Enrico Zio
2022	J	`jnl`	Uncertainty Management and Differential Model Decomposition for Fault Diagnosis and Prognosis. IEEE Trans. Ind. Electron. Dongzhen Lyu, Guangxing Niu, Enhui Liu, Tao Yang, Gang Chen, Bin Zhang
2021	J	`jnl`	Lebesgue-Time-Space-Model-Based Diagnosis and Prognosis for Multiple Mode Systems. IEEE Trans. Ind. Electron. Dongzhen Lyu, Guangxing Niu, Bin Zhang, Gang Chen, Tao Yang
2021	—	`conf`	Uncertainty Analysis in the Application of Fault Diagnosis and Prognosis. ICPS Dongzhen Lyu, Guangxing Niu, Tao Yang, Gang Chen, Bin Zhang
2020	J	`jnl`	Anomaly Detection of Power Plant Equipment Using Long Short-Term Memory Based Autoencoder Neural Network. Sensors Di Hu, Chen Zhang, Tao Yang, Gang Chen
2020	J	`jnl`	Multitask Convolutional Neural Network With Information Fusion for Bearing Fault Diagnosis and Localization. IEEE Trans. Ind. Electron. Sheng Guo, Bin Zhang, Tao Yang, Dongzhen Lyu, Wei Gao
2018	J	`jnl`	A Novel Fault Diagnosis Method for Rotating Machinery Based on a Convolutional Neural Network. Sensors Sheng Guo, Tao Yang, Wei Gao, Chen Zhang
2018	J	`jnl`	An Intelligent Fault Diagnosis Method for Bearings with Variable Rotating Speed Based on Pythagorean Spatial Pyramid Pooling CNN. Sensors Sheng Guo, Tao Yang, Wei Gao, Chen Zhang, Yanping Zhang

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.