Qiancheng Yu - RankMe

17 papers C 1Journal 13Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	An enhancing framework with an emphasis on decision balance in ensemble regression. Neural Networks Xiaoning Li, Min Guo, Qiancheng Yu, Kaiguang Wang, Cai Dai, Zhiqiang Li
2025	J	`jnl`	Refining graph representation: Hyperbolic cross-space diffusion for hierarchical structure preservation. Knowl. Based Syst. Zhirui Chen, Qiancheng Yu, Xiao Chen, Xuchu Jiang
2024	—	`conf`	100 Gbps PAM4 VCSEL-based Transmission over Meter-scale Flexible Multimode Polymer Waveguides for Board-level Optical Interconnects Application. OFC Xu Liu, Lin Ma, Ying Shi, Qiancheng Yu, Motoya Kaneta, Zuyuan He
2024	J	`jnl`	Improved YOLOv8n Model for Detecting Helmets and License Plates on Electric Bicycles. Comput. Mater. Continua Qunyue Mu, Qiancheng Yu, Chengchen Zhou, Lei Liu, Xulong Yu
2023	J	`jnl`	Adaptive Feature Cross-Compression for Credit Default Prediction. IEEE Access Lisi Zhang, Qiancheng Yu, Yifan Zhang, Chengchen Zhou
2023	J	`jnl`	An evolutionary ensemble model based on GA for epidemic transmission prediction. J. Intell. Fuzzy Syst. Xiaoning Li, Qiancheng Yu, Yufan Yang, Chen Tang, Jinyun Wang
2023	J	`jnl`	Application of DeepForest-CQP multi-factor model in quantitative stock selection. J. Intell. Fuzzy Syst. Chen Tang, Qiancheng Yu, Xiaoning Li, Zekun Lu, Yufan Yang
2023	J	`jnl`	Incorporating Feature Interactions and Contrastive Learning for Credit Prediction. IEEE Access Lisi Zhang, Qiancheng Yu, Beijing Zhou, Yifan Zhang, Zhiyong Hu
2023	J	`jnl`	Learning Weight Signed Network Embedding with Graph Neural Networks. Data Sci. Eng. Zekun Lu, Qiancheng Yu, Xia Li, Xiaoning Li, Qinwen Yang
2023	J	`jnl`	Research on tile surface defect detection by improved YOLOv5. J. Intell. Fuzzy Syst. Xulong Yu, Qiancheng Yu, Yue Zhang, Aoqiang Wang, Jinyun Wang
2022	J	`jnl`	Application of Feature Selection Based on Multilayer GA in Stock Prediction. Symmetry Xiaoning Li, Qiancheng Yu, Chen Tang, Zekun Lu, Yufan Yang
2022	C	`conf`	Learning Signed Network Embedding via Muti-attention Mechanism. AAIM Zekun Lu, Qiancheng Yu, Xiaofeng Wang, Xiaoning Li
2022	J	`jnl`	Signed Network Node Embedding via Dual Attention Mechanism. IEEE Access Zekun Lu, Qiancheng Yu, Xia Li, Xiaoning Li, Ao Qiangwang
2020	J	`jnl`	Estimating posterior inference quality of the relational infinite latent feature model for overlapping community detection. Frontiers Comput. Sci. Qiancheng Yu, Zhiwen Yu, Zhu Wang, Xiaofeng Wang, Yongzhi Wang
2019	J	`jnl`	Overlapping community detection for count-value networks. Hum. centric Comput. Inf. Sci. Qiancheng Yu, Zhiwen Yu, Zhu Wang, Xiaofeng Wang, Yongzhi Wang
2018	—	`conf`	A Dependability Modeling and Analysis Approach for an IoP-Based Service System. SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI Zhibao Mian, Leonardo Bottaci, Jiulei Jiang, Jun He, Qiancheng Yu, Xiaofeng Wang
2018	—	`conf`	Constructing the Community Assignment Matrix for Overlapping Community Detection. SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI Qiancheng Yu, Zhiwen Yu, Xiao-Feng Wang

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.