Zheng Wang

13 papers Journal 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A study on hand gesture recognition algorithm realized with the aid of efficient feature extraction method and convolution neural networks: design and its application to VR environment. Soft Comput. Zhen Wang, Sung-Hoon Yoo, Sung-Kwun Oh, Eun-Hu Kim, Zheng Wang, Zunwei Fu, Yuepeng Jiang, Witold Pedrycz
2026	J	`jnl`	BPFNN: Bayesian Probabilistic Fuzzy Neural Networks for Uncertainty-Aware Clustering and Probabilistic Fuzzy Reasoning. IEEE Trans. Cybern. Yunlong Zhu, Haibin Duan, Zheng Wang, Eun-Hu Kim, Zunwei Fu, Witold Pedrycz
2025	J	`jnl`	Corrections to "Robust Classification via Interval Type-2 Fuzzy C-Means and Gradient Boosting". IEEE Trans. Fuzzy Syst. Yunlong Zhu, Haibin Duan, Zheng Wang, Eun-Hu Kim, Zunwei Fu, Witold Pedrycz
2025	J	`jnl`	Robust Classification via Interval Type-2 Fuzzy C-Means and Gradient Boosting. IEEE Trans. Fuzzy Syst. Yunlong Zhu, Haibin Duan, Zheng Wang, Eun-Hu Kim, Zunwei Fu, Witold Pedrycz
2024	J	`jnl`	Design of Tobacco Leaves Classifier Through Fuzzy Clustering-Based Neural Networks With Multiple Histogram Analyses of Images. IEEE Trans. Ind. Informatics Eun-Hu Kim, Zheng Wang, Hao Zong, Ziwu Jiang, Zunwei Fu, Witold Pedrycz
2024	J	`jnl`	Reinforced Fuzzy-Rule-Based Neural Networks Realized Through Streamlined Feature Selection Strategy and Fuzzy Clustering With Distance Variation. IEEE Trans. Fuzzy Syst. Zheng Wang, Eun-Hu Kim, Sung-Kwun Oh, Witold Pedrycz, Zunwei Fu, Jin Hee Yoon
2023	J	`jnl`	Design of progressive fuzzy polynomial neural networks through gated recurrent unit structure and correlation/probabilistic selection strategies. Fuzzy Sets Syst. Zhen Wang, Sung-Kwun Oh, Zheng Wang, Zunwei Fu, Witold Pedrycz, Jin Hee Yoon
2023	J	`jnl`	Noise-Robust Fuzzy Classifier Designed With the Aid of Type-2 Fuzzy Clustering and Enhanced Learning. IEEE Access Ziwu Jiang, Zheng Wang, Eun-Hu Kim
2022	J	`jnl`	Design of Iterative Fuzzy Radial Basis Function Neural Networks Based on Iterative Weighted Fuzzy C-Means Clustering and Weighted LSE Estimation. IEEE Trans. Fuzzy Syst. Seok-Beom Roh, Sung-Kwun Oh, Witold Pedrycz, Zheng Wang, Zunwei Fu, Kisung Seo
2022	J	`jnl`	Design of stabilized fuzzy relation-based neural networks driven to ensemble neurons/layers and multi-optimization. Neurocomputing Zheng Wang, Sung-Kwun Oh, Witold Pedrycz, Eun-Hu Kim, Zunwei Fu
2022	J	`jnl`	Ensemble fuzzy radial basis function neural networks architecture driven with the aid of multi-optimization through clustering techniques and polynomial-based learning. Fuzzy Sets Syst. Cheng Yang, Zheng Wang, Sung-Kwun Oh, Witold Pedrycz, Bo Yang
2022	J	`jnl`	Hierarchically Reorganized Multi-Layer Fuzzy Neural Networks Architecture Driven With the Aid of Node Selection Strategies and Structural Network Optimization. IEEE Access Zheng Wang, Sung-Kwun Oh, Eun-Hu Kim, Zunwei Fu, Witold Pedrycz
2020	J	`jnl`	Robust Multi-Linear Fuzzy SVR Designed With the Aid of Fuzzy C-Means Clustering Based on Insensitive Data Information. IEEE Access Zheng Wang, Cheng Yang, Sung-Kwun Oh, Zunwei Fu, Witold Pedrycz

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.