Feiyun Xiao

14 papers A* 1Journal 11Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Quantitative Analysis of Load Characteristics of Six-Axis Force/Torque Sensor for Robots Based on Dynamic Model. IEEE Trans. Instrum. Meas. Hui Xiao, Aiguo Song, Baoguo Xu, Feiyun Xiao, Yong Wang
2024	J	`jnl`	How to use one surface electromyography sensor to recognize six hand movements for a mechanical hand in real time: a method based on Morse code. Medical Biol. Eng. Comput. Feiyun Xiao, Jingsong Mu, Liangguo He, Yong Wang
2024	J	`jnl`	Research on a Single-Vibrator Multimodal Inertial Impact Piezoelectric Motor With Self-Clamping Backsliding Suppression. IEEE Trans. Ind. Electron. Liangguo He, Xukang Yue, Zengxiang Shan, Chengliang Pan, Liansheng Zhang, Feiyun Xiao
2023	J	`jnl`	A Real-Time Bionic Method Inspired by Neural Oscillators for Estimation and Extraction of Pathological Tremor. IEEE J. Biomed. Health Informatics Feiyun Xiao, Biqing Zhong, Yanming Wu, Yong Wang
2023	J	`jnl`	Human motion intention recognition method with visual, audio, and surface electromyography modalities for a mechanical hand in different environments. Biomed. Signal Process. Control. Feiyun Xiao, Zhen Zhang, Changhai Liu, Yong Wang
2022	J	`jnl`	EWT-IIT: a surface electromyography denoising method. Medical Biol. Eng. Comput. Feiyun Xiao
2021	J	`jnl`	Hand gestures recognition from surface electromyogram signal based on self-organizing mapping and radial basis function network. Biomed. Signal Process. Control. Zhongming Lv, Feiyun Xiao, Zhuang Wu, Zhengshi Liu, Yong Wang
2020	J	`jnl`	Classification of hand movements using variational mode decomposition and composite permutation entropy index with surface electromyogram signals. Future Gener. Comput. Syst. Feiyun Xiao, Decai Yang, Zhongming Lv, Xiaohui Guo, Zhengshi Liu, Yong Wang
2019	J	`jnl`	Motion Estimation From Surface Electromyogram Using Adaboost Regression and Average Feature Values. IEEE Access Feiyun Xiao, Yong Wang, Liangguo He, Hu Wang, Weihan Li, Zhengshi Liu
2018	J	`jnl`	Continuous estimation of joint angle from electromyography using multiple time-delayed features and random forests. Biomed. Signal Process. Control. Feiyun Xiao, Yong Wang, Yongsheng Gao, Yanhe Zhu, Jie Zhao
2016	A*	`conf`	Estimation of tremor parameters and extraction tremor from recorded signals for tremor suppression. ICRA Shengxin Wang, Yongsheng Gao, Feiyun Xiao, Xizhe Zang, Yanhe Zhu, Jie Zhao
2016	J	`jnl`	Prediction of pathological tremor using adaptive multiple oscillators linear combiner. Biomed. Signal Process. Control. Feiyun Xiao, Yongsheng Gao, Shengxin Wang, Jie Zhao
2015	—	`conf`	Analysis and simulation of the neural oscillator for tremor suppression by FES. ROBIO Shengxin Wang, Yongsheng Gao, Feiyun Xiao, Wei Xin, Jie Zhao
2015	—	`conf`	Prediction of joint angle by combining multiple linear regression with autoregressive (AR) model and Kalman filter. ROBIO Feiyun Xiao, Yongsheng Gao, Shengxin Wang, Jie Zhao

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.