Qingmiao Zhang

34 papers C 1Journal 32Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A blockchain-enhanced trust-driven batch authentication scheme for secure VANETs. Ad Hoc Networks Longxia Liao, Junhui Zhao, Qingmiao Zhang, He Fang
2026	J	`jnl`	Channel estimation based on multi-scale generative adversarial networks for RIS-assisted high-speed railway communication systems. Phys. Commun. Qingmiao Zhang, Jihui Wang, Junhui Zhao, Yuhao Zhao
2026	J	`jnl`	Collaborative Computation in Integrated Sensing, Communication, and Computation System for Autonomous Driving. IEEE Trans. Intell. Transp. Syst. Ruixing Ren, Junhui Zhao, Dan Zou, Qingmiao Zhang, Dongming Wang, Wei Xu
2026	J	`jnl`	Deep Reinforcement Learning-Based Task Offloading and Migration for Rail Transit. IEEE Trans. Veh. Technol. Junhui Zhao, Xu Gao, Lin He, Qingmiao Zhang, Haitao Han
2026	J	`jnl`	Green-Edge Computing-Based IoV Dynamic Task Collaborative Strategy. IEEE Trans. Green Commun. Netw. Pingzheng Ge, Haoyu Quan, Qingmiao Zhang, Junhui Zhao
2026	J	`jnl`	UAV-Assisted Collaborative Sensing Task Offloading and Resource Allocation in IoV. IEEE Trans. Veh. Technol. Ruixing Ren, Junhui Zhao, Qingmiao Zhang
2025	J	`jnl`	A reconstruction and recovery network-based channel estimation in high-speed railway wireless communications. Digit. Commun. Networks Qingmiao Zhang, Yuhao Zhao, Hanzhi Dong, Junhui Zhao
2025	J	`jnl`	Computation Offloading Optimization for Digital Twin Assisted 5G-Enabled Edge Computing Network in Urban Rail Transit. IEEE Trans. Intell. Transp. Syst. Qingmiao Zhang, Minghao Liu, Junhui Zhao, Chenxi Zhang, Ming Zhang
2025	J	`jnl`	DRL Beamforming in RIS-Aided IoV for Integrated-Sensing-Communication-Computation. IEEE Internet Things J. Ruixing Ren, Junhui Zhao, Qingmiao Zhang, Dongming Wang, Jiamin Li
2025	J	`jnl`	Dynamic Resource Allocation for Multi-Access Edge Computing in Urban Rail Transit. IEEE Trans. Veh. Technol. Qingmiao Zhang, Chenxi Zhang, Junhui Zhao, Dongming Wang, Wei Xu
2025	J	`jnl`	Edge Server and Service Deployment Considering Profit With Improved PSO in IoV. IEEE Syst. J. Junhui Zhao, Yuwen Huang, Qingmiao Zhang, Dongming Wang, Wei Xu
2025	J	`jnl`	Federated Learning Assisted Intelligent IoV Mobile Edge Computing. IEEE Trans. Green Commun. Netw. Haoyu Quan, Qingmiao Zhang, Junhui Zhao
2025	J	`jnl`	Fog-Based Authentication and Key Agreement Protocol for Internet of Autonomous Vehicle. IEEE Internet Things J. Junhui Zhao, Jingyan Chen, Longxia Liao, Qingmiao Zhang
2025	J	`jnl`	Low-Latency V2X Communication With Non-Orthogonal Slicing: A Deterministic Network Calculus Approach. IEEE Trans. Veh. Technol. Yuyu Liu, Junhui Zhao, Minghua Xia, Qingmiao Zhang
2025	J	`jnl`	Offloading Strategy of Green Edge Computing Based on Idle Roadside Devices Collaboration. IEEE Syst. J. Pingzheng Ge, Dan Zou, Qingmiao Zhang, Junhui Zhao
2025	J	`jnl`	SEAttention-residual based channel estimation for mmWave massive MIMO systems in IoV scenarios. Digit. Commun. Networks Junhui Zhao, Ruixing Ren, Yao Wu, Qingmiao Zhang, Wei Xu, Dongming Wang, Lisheng Fan
2024	J	`jnl`	Artificial intelligence in rail transit wireless communication systems: Status, challenges and solutions. Phys. Commun. Junhui Zhao, Xu Gao, Zhengyuan Wu, Qingmiao Zhang, Haitao Han
2024	J	`jnl`	Blockchain-Based Trust Management Model for Vehicular Ad Hoc Networks. IEEE Internet Things J. Junhui Zhao, Fanwei Huang, Longxia Liao, Qingmiao Zhang
2024	J	`jnl`	Boosting vehicular connectivity through resource allocation algorithm based on Heterogeneous Agent Proximal Policy Optimization. Veh. Commun. Junhui Zhao, Xincheng Xiong, Qingmiao Zhang, Shihai Ren, Jingyan Chen, Wei Xu, Dongming Wang
2024	J	`jnl`	Extended Multi-Component Gated Recurrent Graph Convolutional Network for Traffic Flow Prediction. IEEE Trans. Intell. Transp. Syst. Junhui Zhao, Xincheng Xiong, Qingmiao Zhang, Dongming Wang
2024	J	`jnl`	IoV-Oriented Integrated Sensing, Computation, and Communication: System Design and Resource Allocation. IEEE Trans. Veh. Technol. Junhui Zhao, Ruixing Ren, Dan Zou, Qingmiao Zhang, Wei Xu
2024	J	`jnl`	MEC-enabled resource allocation in Internet of Vehicles. Phys. Commun. Yijing Xiao, Junhui Zhao, Qingmiao Zhang, Yuwen Huang, Haoyu Quan, Lisheng Fan
2024	J	`jnl`	Mobile association scheme based on auction algorithm in heterogeneous wireless networks. Ad Hoc Networks Junhui Zhao, Xuehan Bao, Hongyi Bian, Qingmiao Zhang, Dongming Wang, Lisheng Fan
2024	J	`jnl`	Optimization of resource allocation strategy for high-speed railway based on deep reinforcement learning. Phys. Commun. Xu Gao, Junhui Zhao, Qingmiao Zhang, Haitao Han
2023	J	`jnl`	Constrained DRL for Energy Efficiency Optimization in RSMA-Based Integrated Satellite Terrestrial Network. Sensors Qingmiao Zhang, Lidong Zhu, Yanyan Chen, Shan Jiang
2023	J	`jnl`	ResNet-WGAN-Based End-to-End Learning for IoV Communication With Unknown Channels. IEEE Internet Things J. Junhui Zhao, Huiqin Mu, Qingmiao Zhang, Huan Zhang
2023	J	`jnl`	Two-Stage Channel Estimation for mmWave Massive MIMO Systems Based on ResNet-UNet. IEEE Syst. J. Junhui Zhao, Yao Wu, Qingmiao Zhang, Jieyu Liao
2022	C	`conf`	A Deep Learning Approach for Downlink Sum Rate Maximization in Satellite-Terrestrial Integrated Network. ISNCC Qingmiao Zhang, Lidong Zhu
2022	J	`jnl`	Intelligent train control for cooperative train formation: A deep reinforcement learning approach. J. Syst. Control. Eng. Danyang Zhang, Junhui Zhao, Yang Zhang, Qingmiao Zhang
2022	J	`jnl`	RAT selection for IoT devices in HetNets: Reinforcement learning with hybrid SMDP algorithm. Phys. Commun. Hongyi Bian, Qingmiao Zhang, Junhui Zhao, Huan Zhang
2021	J	`jnl`	Cluster-based energy-efficient joint user association and resource allocation for B5G ultra-dense network. Phys. Commun. Lin Zhu, Lihua Yang, Qingmiao Zhang, Tianqing Zhou, Jun Hua
2020	—	`conf`	Joint 3D Trajectory and Power Optimization for Multiple Antenna Aided NOMA in UAV Networks. WCSP Jie Tang, Wanmei Feng, Qingmiao Zhang, Jun-hui Ou, Xiuyin Zhang, Junhui Zhao
2019	J	`jnl`	A Novel QoS-Awared Grid Routing Protocol in the Sensing Layer of Internet of Vehicles Based on Reinforcement Learning. IEEE Access Denghui Wang, Qingmiao Zhang, Jian Liu, Dezhong Yao
2019	J	`jnl`	Pilot contamination reduction in TDD-based massive MIMO systems. IET Commun. Junhui Zhao, Shanjin Ni, Yi Gong, Qingmiao Zhang

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.