Yangtao Li - RankMe

13 papers Journal 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	DSRCAM-ICRF: A weakly supervised framework for crack segmentation in hydraulic concrete structures. Adv. Eng. Informatics Mengfan Zhao, Tengfei Bao, Yangtao Li, Chengbo Fan, Yunlin Ma, Yang Wei
2026	J	`jnl`	TSDR-SFE: A prediction model for dam crack width based on two-stage decomposition-reconstruction and spatiotemporal feature extraction. Adv. Eng. Informatics Yixiang Fang, Chongshi Gu, Yangtao Li, Yiming Wang, Taiqi Lu, Lei Shen, Xiao Sun, Mingyuan Zhu, Fuqiang Zhou, Sitao Fu, Hao Gu
2025	J	`jnl`	A framework for automatic Real-Time Pixel-Level segmentation of underwater dam concrete cracks utilizing the CRTransU-Net model. Adv. Eng. Informatics Yunlin Ma, Tengfei Bao, Yangtao Li, Mengfan Zhao
2025	J	`jnl`	Automated defect segmentation and quantification in concrete structures via unmanned aerial vehicle-based lightweight deep learning. Comput. Aided Civ. Infrastructure Eng. Yangtao Li, Haitao Zhao, Hao Gu, Yang Wei, Zhenyang Xiang, Yiming Wang, Yang Yu, Tengfei Bao
2025	J	`jnl`	Environmental-aware deformation prediction of water-related concrete structures using deep learning. Comput. Aided Civ. Infrastructure Eng. Hao Gu, Yangtao Li, Yixiang Fang, Yiming Wang, Yang Yu, Yang Wei, Liqun Xu, Yijun Chen
2025	J	`jnl`	GANFormerNet: A UAV-based Concrete Crack Segmentation Model for Water-related Structures Using Vision Transformer and Graph Attention Network. Adv. Eng. Informatics Yunlin Ma, Tengfei Bao, Yangtao Li, Mengfan Zhao, Zhenhao Wu, Chengbo Fan
2025	J	`jnl`	Symmetric Integrability and Linearizability of Weak Saddles in Planar Cubic Differential Systems. Math. Comput. Sci. Yusen Wu, Yangtao Li, Xinli Li, Xiangyu Wang
2023	J	`jnl`	A robust real-time method for identifying hydraulic tunnel structural defects using deep learning and computer vision. Comput. Aided Civ. Infrastructure Eng. Yangtao Li, Tengfei Bao, Tianyu Li, Ruijie Wang
2023	J	`jnl`	Multi-expert attention network for long-term dam displacement prediction. Adv. Eng. Informatics Yuhang Zhou, Tengfei Bao, Guoli Li, Xiaosong Shu, Yangtao Li
2022	J	`jnl`	VAE-TALSTM: a temporal attention and variational autoencoder-based long short-term memory framework for dam displacement prediction. Eng. Comput. Xiaosong Shu, Tengfei Bao, Yangtao Li, Jian Gong, Kang Zhang
2021	J	`jnl`	A Novel Seepage Behavior Prediction and Lag Process Identification Method for Concrete Dams Using HGWO-XGBoost Model. IEEE Access Kang Zhang, Chongshi Gu, Yantao Zhu, Siyu Chen, Bo Dai, Yangtao Li, Xiaosong Shu
2020	J	`jnl`	Dam Safety Evaluation Based on Interval-Valued Intuitionistic Fuzzy Sets and Evidence Theory. Sensors Xiaosong Shu, Tengfei Bao, Yangtao Li, Kang Zhang, Bangbin Wu
2020	J	`jnl`	The Prediction of Dam Displacement Time Series Using STL, Extra-Trees, and Stacked LSTM Neural Network. IEEE Access Yangtao Li, Tengfei Bao, Jian Gong, Xiaosong Shu, Kang 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.

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.