Qiuyue Li - RankMe

17 papers C 5Journal 10Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Midnet: multi-scale interaction guided adaptive discretization network for monocular depth estimation. Int. J. Mach. Learn. Cybern. Long Yan, Qiuyue Li, Zhiyao Li, Fuyang Yu
2025	J	`jnl`	Enhancing road surface recognition via optimal transport and metric learning in task-agnostic intelligent driving environments. Expert Syst. Appl. Yuyi Chen, Shichun Yang, Rui Wang, Zhuoyang Li, Qiuyue Li, Zexiang Tong, Yaoguang Cao, Fan Zhou
2025	C	`conf`	RaLMEN: A Robust UAV Recognition Framework for Low-Altitude Traffic Surveillance. INDIN Mohan Xu, Gaoyuan Yang, Yuting Jia, Qiuyue Li, Qingyun Ye, Haowei Wu, Xiaoyu Yan
2024	C	`conf`	A Safety Assessment Method Based on Cloud Model for Decision-making of Autonomous Vehicles. INDIN Shichun Yang, Qiuyue Li, Zhaowen Pang, Bin Sun, Xinjie Feng, Rui Wang, Tianyang Gong, Yaoguang Cao
2024	—	`conf`	Daformer: A Novel Dimension-Augmented Transformer Framework for Multivariate Time Series Forecasting. ICIC (LNAI 2) Yongfeng Su, Juhui Zhang, Qiuyue Li
2024	C	`conf`	Domain Adaptation for Semantic Segmentation of Autonomous Driving with Contrastive Learning. INDIN Qiuyue Li, Shichun Yang, Mohan Xu, Bingtao Ren, Xiaoyu Yan, Fan Zhou
2024	J	`jnl`	Graph Alignment Neural Network Model With Graph to Sequence Learning. IEEE Trans. Knowl. Data Eng. Nianwen Ning, Bin Wu, Haoqing Ren, Qiuyue Li
2024	J	`jnl`	OSTNet: overlapping splitting transformer network with integrated density loss for vehicle density estimation. Appl. Intell. Yang Qu, Liran Yang, Ping Zhong, Qiuyue Li
2024	J	`jnl`	SCSformer: cross-variable transformer framework for multivariate long-term time series forecasting via statistical characteristics space. Appl. Intell. Yongfeng Su, Juhui Zhang, Qiuyue Li
2022	J	`jnl`	A Model Study on Hierarchical Assisted Exploration of RBAC. Int. J. Digit. Crime Forensics Wan Chen, Daojun Han, Lei Zhang, Qi Xiao, Qiuyue Li, Hongzhen Xiang
2021	C	`conf`	Embedding-Based Network Alignment Using Neural Tensor Networks. KSEM Qiuyue Li, Nianwen Ning, Bin Wu, WenYing Guo
2021	J	`jnl`	Multiplex Network Embedding Model with High-Order Node Dependence. Complex. Nianwen Ning, Qiuyue Li, Kai Zhao, Bin Wu
2021	C	`conf`	Online Knowledge Distillation via Collaborative Learning with Enhanced Diversity and Gradual Ensemble. IWCIA Qiuyue Li, Motonobu Hattori, Wei Zhang, Zhigang Gao
2021	J	`jnl`	Wideband spectrum sensing based on modulated wideband converter with nested array. IET Commun. Qiuyue Li, Zhi Li, Jian Li
2019	—	`conf`	KSC: A Fast and Simple Spectral Clustering Algorithm. DSC Longcheng Zhai, Bin Wu, Qiuyue Li
2018	J	`jnl`	Positive solutions to superlinear attractive singular impulsive differential equation. Appl. Math. Comput. Qiuyue Li, Yaoming Zhou, Fuzhong Cong, Hu Liu
2008	J	`jnl`	Multiplicity of positive solutions to second order Neumann boundary value problems with impulse actions. Appl. Math. Comput. Qiuyue Li, Fuzhong Cong, Daqing Jiang

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.