Qiao Yuan - RankMe

14 papers C 1Journal 9Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Class-incremental continual graph learning with adversarial graph condensation. Neurocomputing Qiao Yuan, Boxuan Zhu, Sheng-Uei Guan, Ka Lok Man, Prudence W. H. Wong
2026	J	`jnl`	Continual graph learning: A survey. Pattern Recognit. Qiao Yuan, Sheng-Uei Guan, Pin Ni, Tianlun Luo, Prudence W. H. Wong, Victor Chang, Ka Lok Man
2026	J	`jnl`	Towards Secure Retrieval-Augmented Generation: A Comprehensive Review of Threats, Defenses and Benchmarks. CoRR Yanming Mu, Hao Hu, Feiyang Li, Qiao Yuan, Jiang Wu, Zichuan Liu, Pengcheng Liu, Mei Wang, Hongwei Zhou, Yuling Liu
2025	J	`jnl`	Exploring interaction concepts for human-object-interaction detection via global- and local-scale enhancing. Neurocomputing Tianlun Luo, Qiao Yuan, Boxuan Zhu, Steven Guan, Rui Yang, Jeremy S. Smith, Eng Gee Lim
2025	J	`jnl`	IMCGNN: Information Maximization based Continual Graph Neural Networks for inductive node classification. Neurocomputing Qiao Yuan, Sheng-Uei Guan, Tianlun Luo, Ka Lok Man, Eng Gee Lim
2025	J	`jnl`	Recurrent fusion transformer for image captioning. Signal Image Video Process. Zhenping Mou, Qiao Yuan, Tianqi Song
2025	J	`jnl`	Simple yet effective: An explicit query-based relation learner for human-object-interaction detection. Neurocomputing Tianlun Luo, Qiao Yuan, Boxuan Zhu, Steven Sheng-Uei Guan, Rui Yang, Jeremy S. Smith, Eng Gee Lim
2024	—	`conf`	Research on automatic execution system of power emergency plan based on artificial intelligence. CSAIDE Lifeng Wang, Yongguang Niu, Zhimin Shao, Qiao Yuan, Bo Liu, Shipeng Hou
2023	J	`jnl`	Continual Graph Learning: A Survey. CoRR Qiao Yuan, Sheng-Uei Guan, Pin Ni, Tianlun Luo, Ka Lok Man, Prudence W. H. Wong, Victor Chang
2023	—	`conf`	Design of a Data Transmission Control Unit in a Multi-core DSP System. ASICON Hu Ge, Qiao Yuan, Yuhao Zhang, Yukun Song, Zhenmin Li
2023	J	`jnl`	QS-ADN: Quasi-Supervised Artifact Disentanglement Network for Low-Dose CT Image Denoising by Local Similarity Among Unpaired Data. CoRR Yuhui Ruan, Qiao Yuan, Chuang Niu, Chen Li, Yudong Yao, Ge Wang, Yueyang Teng
2022	C	`conf`	A Spatial-Channel Attention-Based Convolutional Neural Network for Remote Sensing Image Classification. IGARSS Yuanzhen Shuai, Qiao Yuan, Shanshan Zhao
2022	—	`conf`	Eigenvector-based Graph Neural Network Embeddings and Trust Rating Prediction in Bitcoin Networks. ICAIF Pin Ni, Qiao Yuan, Raad Khraishi, Ramin Okhrati, Aldo Lipani, Francesca Medda
2019	—	`conf`	The Design and Implementation of High Speed Hybrid Radices Reconfigurable FFT Processor. ASICON Qiao Yuan, Huajian Zhang, Yukun Song, Chongyang Li, Xueyi Liu, Zheng Yan

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.