Qihong Yang - RankMe

16 papers A* 1A 1Journal 10Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A novel Fourier feature network for solving partial differential equations. Commun. Nonlinear Sci. Numer. Simul. Qihong Yang, Zhijie Su, Yangtao Deng, Qiaolin He
2024	J	`jnl`	Moving sampling physics-informed neural networks induced by moving mesh PDE. Neural Networks Yu Yang, Qihong Yang, Yangtao Deng, Qiaolin He
2024	J	`jnl`	Multi-Modal MR Image Segmentation Strategy for Brain Tumors Based on Domain Adaptation. Comput. Qihong Yang, Ruijun Jing, Jiliang Mu
2024	J	`jnl`	Solving Multi-Group Neutron Diffusion Eigenvalue Problem with Decoupling Residual Loss Function. CoRR Shupei Yu, Qiaolin He, Shiquan Zhang, Qihong Yang, Yu Yang, Helin Gong
2024	—	`conf`	Study on the diffusion law of typical floating pollutants in inland waters. CAIBDA Lin Zhang, Zhaohui Chai, Qihong Yang, Fengyang Min
2023	J	`jnl`	FDM-PINN: Physics-informed neural network based on fictitious domain method. Int. J. Comput. Math. Qihong Yang, Yu Yang, Tao Cui, Qiaolin He
2023	J	`jnl`	MMPDE-Net and Moving Sampling Physics-informed Neural Networks Based On Moving Mesh Method. CoRR Yu Yang, Qihong Yang, Yangtao Deng, Qiaolin He
2023	J	`jnl`	Neural networks based on power method and inverse power method for solving linear eigenvalue problems. Comput. Math. Appl. Qihong Yang, Yangtao Deng, Yu Yang, Qiaolin He, Shiquan Zhang
2022	J	`jnl`	Neural Networks Base on Power Method and Inverse Power Method for Solving Linear Eigenvalue Problems. CoRR Qihong Yang, Yangtao Deng, Yu Yang, Qiaolin He, Shiquan Zhang
2021	A	`conf`	Denoising User-aware Memory Network for Recommendation. RecSys Zhi Bian, Shaojun Zhou, Hao Fu, Qihong Yang, Zhenqi Sun, Junjie Tang, Guiquan Liu, Kaikui Liu, Xiaolong Li
2021	J	`jnl`	Denoising User-aware Memory Network for Recommendation. CoRR Zhi Bian, Shaojun Zhou, Hao Fu, Qihong Yang, Zhenqi Sun, Junjie Tang, Guiquan Liu, Kaikui Liu, Xiaolong Li
2021	A*	`conf`	LRC-BERT: Latent-representation Contrastive Knowledge Distillation for Natural Language Understanding. AAAI Hao Fu, Shaojun Zhou, Qihong Yang, Junjie Tang, Guiquan Liu, Kaikui Liu, Xiaolong Li
2020	J	`jnl`	LRC-BERT: Latent-representation Contrastive Knowledge Distillation for Natural Language Understanding. CoRR Hao Fu, Shaojun Zhou, Qihong Yang, Junjie Tang, Guiquan Liu, Kaikui Liu, Xiaolong Li
2018	—	`conf`	An Image Matching Algorithm based on Mutual Information for Small Dimensionality Target. ICNC-FSKD Qihong Yang, Qiang Wei
2017	—	`conf`	Analysis on the performance of several data association algorithms using Doppler information. ICNC-FSKD Qiang Wei, Qihong Yang, Zhong Liu
2017	—	`conf`	DP-MFTD algorithm based on the conditional probability ratio accumulation model. ICNC-FSKD Qiang Wei, Qihong Yang, Zhong Liu

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.