Fan Deng - RankMe

15 papers Journal 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AFMT: Adaptive frequency decomposition and multi-scale transformer for time series forecasting. Inf. Sci. Li Zhu, Wanru Xu, Chunqiang Zhu, Jingkai Gao, Lugema Mi, Fan Deng, Jinqi Qu
2025	J	`jnl`	MSRNet: Multi-level series decomposition and stepwise reconstruction network for load forecasting. J. King Saud Univ. Comput. Inf. Sci. Li Zhu, Jingkai Gao, Chunqiang Zhu, Fan Deng, Jiarui He
2025	J	`jnl`	Short-term power load forecasting based on spatial-temporal dynamic graph and multi-scale Transformer. J. Comput. Des. Eng. Li Zhu, Jingkai Gao, Chunqiang Zhu, Fan Deng
2023	J	`jnl`	Integrating deep neural network with logic rules for credit scoring. Intell. Data Anal. Zhanli Li, Xinyu Zhang, Fan Deng, Yun Zhang
2022	J	`jnl`	ANNPDP: An Efficient and Stable Evaluation Engine for Large-Scale Policy Sets. IEEE Trans. Serv. Comput. Fan Deng, Zhenhua Yu, Liyong Zhang, Jiawei Wang, Kexin Feng, Wenbin Kong, Lingyu Li, Jiawen Wu
2022	J	`jnl`	Improvement on PDP Evaluation Performance Based on Neural Networks and SGDK-means Algorithm. Soft Comput. Fan Deng, Zhenhua Yu, Houbing Song, Liyong Zhang, Xi Song, Min Zhang, Zhenyu Zhang, Yu Mei
2022	J	`jnl`	Parallel double-layer prediction model construction and empirical analysis for enterprise credit assessment. Intell. Data Anal. Zhanli Li, Linchao Liu, Li Zhu, Fan Deng, Yun Zhang, Yu Zhang
2021	J	`jnl`	An efficient policy evaluation engine for XACML policy management. Inf. Sci. Fan Deng, Zhenhua Yu, Wenjing Liu, Xiaoqing Luo, Yu Fu, Ben Qiang, Chaoyang Xu, ZhiWu Li
2021	J	`jnl`	An efficient policy evaluation engine with locomotive algorithm. Clust. Comput. Fan Deng, Zhenhua Yu, Houbing Song, Rongyi Zhao, Qi Zheng, Zhenyu Li, Huansheng He, Yixin Zhang, Fangzhi Guo
2020	J	`jnl`	A Graph and Clustering-Based Framework for Efficient XACML Policy Evaluation. Int. J. Cooperative Inf. Syst. Yanfei Li, Fan Deng
2020	J	`jnl`	Clustering and supervised response for XACML policy evaluation and management. Knowl. Based Syst. Fan Deng, Zhenhua Yu, Liyong Zhang, Xiaodong Ge, Ruiyu Zhao, Xiaotong Li, Yuhao Ma, Yang Yan, Zhe Wen
2019	J	`jnl`	A distributed PDP model based on spectral clustering for improving evaluation performance. World Wide Web Fan Deng, Jie Lu, Shi-Yu Wang, Jie Pan, Li-Yong Zhang
2019	J	`jnl`	Establishment of rule dictionary for efficient XACML policy management. Knowl. Based Syst. Fan Deng, Liyong Zhang, Changyu Zhang, Hao Ban, Chang-Dong Wang, Minghao Shi, Chao Chen, Enti Zhang
2018	J	`jnl`	Establishment of attribute bitmaps for efficient XACML policy evaluation. Knowl. Based Syst. Fan Deng, Shiyu Wang, Liyong Zhang, Xiaoqian Wei, Jingping Yu
2017	J	`jnl`	Elimination of policy conflict to improve the PDP evaluation performance. J. Netw. Comput. Appl. Fan Deng, Li-Yong 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.