Lechan Yang

15 papers Journal 14Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	TGAIN: Geospatial Data Recovery Algorithm Based on GAIN-LSTM. Comput. Mater. Continua Lechan Yang, Li Li, Shouming Ma
2023	J	`jnl`	Intrusion detection model using gene expression programming to optimize parameters of convolutional neural network for energy internet. Appl. Soft Comput. Song Deng, Xinya Yuan, Qianliang Li, Jie Zhang, Mengfei Sun, Xiong Fu, Lechan Yang
2023	—	`conf`	Research on Data Transmission Security Risk Assessment Mechanism for Geospatial. PCCNT Lechan Yang
2022	J	`jnl`	Estimation model of leaf nitrogen content based on GEP and leaf spectral reflectance. Comput. Electr. Eng. Lechan Yang, Song Deng, Shouming Ma, Fangxiong Xiao
2021	J	`jnl`	Finger Gesture Recognition Using Sensing and Classification of Surface Electromyography Signals With High-Precision Wireless Surface Electromyography Sensors. Frontiers Comput. Neurosci. Jianting Fu, Shizhou Cao, Linqin Cai, Lechan Yang
2020	J	`jnl`	Data filter function incremental mining based on feature selection in an active distribution network. IET Cyper-Phys. Syst.: Theory & Appl. Song Deng, Qingyuan Cai, Zi Zhang, Lechan Yang, Tinglei Huang, Changan Yuan
2020	J	`jnl`	New spectral model for estimating leaf area index based on gene expression programming. Comput. Electr. Eng. Lechan Yang, Song Deng, Zi Zhang
2020	J	`jnl`	Numerical sensitive data recognition based on hybrid gene expression programming for active distribution networks. Appl. Soft Comput. Song Deng, Xiangpeng Xie, Chang-An Yuan, Lechan Yang, Xindong Wu
2019	J	`jnl`	A Novel Function Mining Algorithm Based on Attribute Reduction and Improved Gene Expression Programming. IEEE Access Changan Yuan, Xiao Qin, Lechan Yang, Guangwei Gao, Song Deng
2019	J	`jnl`	Data recovery algorithm under intrusion attack for energy internet. Future Gener. Comput. Syst. Song Deng, Changan Yuan, Lechan Yang, Xiao Qin, Aihua Zhou
2018	J	`jnl`	Distributed correlation model mining from remote sensing big data based on gene expression programming. Peer-to-Peer Netw. Appl. Lechan Yang, Zhihao Qin
2018	J	`jnl`	Distributed electricity load forecasting model mining based on hybrid gene expression programming and cloud computing. Pattern Recognit. Lett. Song Deng, Changan Yuan, Lechan Yang, Liping Zhang
2017	J	`jnl`	Distributed content filtering algorithm based on data label and policy expression in active distribution networks. Neurocomputing Song Deng, Dong Yue, Aihua Zhou, Xiong Fu, Lechan Yang, Yu Xue
2017	J	`jnl`	Identifying the Lambertian Property of Ground Surfaces in the Thermal Infrared Region via Field Experiments. Remote. Sens. Lili Tu, Zhihao Qin, Lechan Yang, Fei Wang, Jun Geng, Shuhe Zhao
2016	J	`jnl`	Reliable H Neurocomputing Song Deng, Lechan Yang

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.