Panfeng Zhang

14 papers B 1Journal 8Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	SRM-LLM: Semantic Relationship Mining with LLMs for Temporal Knowledge Graph Extrapolation. EMNLP (Findings) Fu Zhang, Panfeng Zhang, Jingwei Cheng
2024	J	`jnl`	Computing Resource Allocation Strategy Based on Cloud-Edge Cluster Collaboration in Internet of Vehicles. IEEE Access Xianhao Shen, Li Wang, Panfeng Zhang, Xiaolan Xie, Yi Chen, Shaofang Lu
2024	—	`conf`	Hydrate Management in Subsea Production System During Deep Water Gas Field Development by a Comprehensive Calculation Model. ICCBD Panfeng Zhang, Jing Zhu, Wenfeng Chen, Shubing Zeng, Chenglong Yu
2024	J	`jnl`	The Influence of Local Climatic Factors and Water Vapor Transport from North Atlantic Ocean on Winter Snow-Cover Variation on Western Kunlun Mountains and Eastern Pamir Plateau. Remote. Sens. Xiaoying Xue, Xiangde Xu, Guoyu Ren, Xiubao Sun, Panfeng Zhang
2023	J	`jnl`	DPBA-WGAN: A Vector-Valued Differential Private Bilateral Alternative Scheme on WGAN for Image Generation. IEEE Access Danhua Wu, Wenyong Zhang, Panfeng Zhang
2023	J	`jnl`	Deep Reinforcement Learning-Based Intelligent Reflecting Surface for Cooperative Jamming Model Design. IEEE Access Shaofang Lu, Xianhao Shen, Panfeng Zhang, Zhen Wu, Yi Chen, Li Wang, Xiaolan Xie
2023	J	`jnl`	Joint optimization of UAV-WPT and mixed task offloading strategies with shared mode in SAG-PIoT: A MAD4PG approach. Internet Things Yi Chen, Xianhao Shen, Panfeng Zhang, Shaofang Lu, Li Wang, Zhen Wu, Xiaolan Xie
2023	J	`jnl`	Traffic Flow Prediction Based on Information Aggregation and Comprehensive Temporal-Spatial Synchronous Graph Neural Network. IEEE Access Xiaohui Cheng, Yuhao He, Panfeng Zhang, Yanping Kang
2022	—	`conf`	Dif-NoBa A differential privacy noise Bayesian gradient descent algorithm in Deep Learning. ICIIP Panfeng Zhang, Danhua Wu, Zhiwei Yang
2022	—	`conf`	privacy protection method for deep learning based on local random nodes. ICIIP Panfeng Zhang, Wenyong Zhang
2018	J	`jnl`	A New Methodology for Estimating the Surface Temperature Lapse Rate Based on Grid Data and Its Application in China. Remote. Sens. Yun Qin, Guoyu Ren, Tianlin Zhai, Panfeng Zhang, Kangmin Wen
2017	J	`jnl`	Resemblance and mergence based indexing for high performance data deduplication. J. Syst. Softw. Panfeng Zhang, Ping Huang, Xubin He, Hua Wang, Ke Zhou
2016	B	`conf`	RMD: A Resemblance and Mergence Based Approach for High Performance Deduplication. ICPP Panfeng Zhang, Ping Huang, Xubin He, Hua Wang, Lingyu Yan, Ke Zhou
2015	—	`conf`	Weighted association rule mining based on PCA algorithm in wireless communication network. ChinaCom Panfeng Zhang, Shilian Wang, Eryang Zhang, Fangping Liu

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.