Qu Wei

11 papers Journal 10Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Deep Reinforcement Learning-Based Hyper-Heuristic for Time-Dependent Green Logistics With Crowdsourcing. IEEE Trans. Intell. Transp. Syst. Chu Tang, Qu Wei, Jingbin He, Guido Perboli, Hu Qin, Kang Li
2026	J	`jnl`	A hybrid adaptive large neighborhood search with sample average approximation for elective and clinically urgent surgery scheduling under uncertainty. Appl. Soft Comput. Li Lu, Qu Wei, Jing Xie, Chu Tang, Cui Yang, Kang Li
2026	J	`jnl`	An adaptive large neighborhood search algorithm with customized search operators for solving home healthcare scheduling and routing problems with skill matching and periodic visits. Appl. Soft Comput. Benjie Li, Jingmei Pan, Qu Wei
2026	J	`jnl`	An adaptive large neighborhood search with dynamic exit reassignment for guided multi-story hospital fire evacuation. Inf. Sci. Li Zhou, Qu Wei, Yikun Yang, Ruisan Zhang, Hao Yu, Zhaoxia Guo, Kang Li
2026	J	`jnl`	Enhancing knee contact force prediction using transformer networks: A comparative study with LSTM and MLP. Biomed. Signal Process. Control. Fashu Xu, Junqing Wang, Bingkui Tong, Xuyi Fang, Hui Zhang, Tao Deng, Qu Wei, Yong Nie, Kang Li
2025	J	`jnl`	Topological representation based on wavelet transform as a novel imaging biomarker for tumor diagnosis in ultrasound images: A comprehensive study. Comput. Methods Programs Biomed. Qu Wei, Si Zeng, Zekun Jiang, Fashu Xu, Shuhua Shi, Wen Wen, Ziyuan Qin, Zhenye Lou, Kang Li
2024	—	`conf`	EEG-DIF: Early Warning of Epileptic Seizures through Generative Diffusion Model-based Multi-channel EEG Signals Forecasting. BCB Zekun Jiang, Wei Dai, Qu Wei, Ziyuan Qin, Kang Li, Le Zhang
2024	J	`jnl`	EEG-DIF: Early Warning of Epileptic Seizures through Generative Diffusion Model-based Multi-channel EEG Signals Forecasting. CoRR Zekun Jiang, Wei Dai, Qu Wei, Ziyuan Qin, Kang Li, Le Zhang
2022	J	`jnl`	A Simulation-Optimization Approach for the Management of the On-Demand Parcel Delivery in Sharing Economy. IEEE Trans. Intell. Transp. Syst. Guido Perboli, Mariangela Rosano, Qu Wei
2021	J	`jnl`	A bi-objective stochastic order planning problem in make-to-order multi-site textile manufacturing. Comput. Ind. Eng. Zhenzhong Zhang, Chunxiang Guo, Qu Wei, Zhaoxia Guo, Lei Gao
2019	J	`jnl`	An artificial bee colony-based hybrid approach for waste collection problem with midway disposal pattern. Appl. Soft Comput. Qu Wei, Zhaoxia Guo, Hoong Chuin Lau, Zhenggang He

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.

In 2025, he co-authored Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja, published at CheckMATE. The paper evaluates the effectiveness of obfuscation techniques and their impact on source-level static analysis and binary-level decompilation.

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.