Yan Ding - RankMe

27 papers A* 1C 1Journal 24Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Hybrid deep reinforcement learning-based workload migrating and resource allocation policies for weighted cost minimization in edge collaboration networks. Future Gener. Comput. Syst. Hongchang Ke, Jia Zhao, Yan Ding, Lin Pan
2026	J	`jnl`	The Wonderful Flower of Seven Colors: Self-Evolution Approach for Multi-Terminal Personalized Service Processing. IEEE Trans. Serv. Comput. Jia Zhao, Yafei Zhu, Keqin Li, Ming Hu, Yan Ding
2025	J	`jnl`	ADAMT: Adaptive distributed multi-task learning for efficient image recognition in Mobile Ad-hoc Networks. Neural Networks Jia Zhao, Wei Zhao, Yunan Zhai, Liyuan Zhang, Yan Ding
2025	J	`jnl`	Adaptive feature fusion and task-dynamic alignment for real-time object detection on edge devices. Expert Syst. Appl. Yan Ding, Wenjie Wu, Yunan Zhai, Liyuan Zhang, Lin Pan, Jia Zhao
2025	A*	`conf`	Modular Deep Reinforcement Learning for Multi-Workload Offloading in Edge Networks. IJCAI Hongchang Ke, Yan Ding, Lin Pan, Yang Chen, Jia Zhao
2025	J	`jnl`	Optimizing mobile blockchain networks: A game theoretical approach to cooperative multi-terminal computation. Future Gener. Comput. Syst. Lin Pan, Fengrui Chen, Yan Ding, Yunan Zhai, Liyuan Zhang, Jia Zhao
2023	J	`jnl`	Deep forest auto-Encoder for resource-Centric attributes graph embedding. Pattern Recognit. Yan Ding, Yujuan Zhai, Ming Hu, Jia Zhao
2023	J	`jnl`	Integrate computation intelligence with Bayes theorem into complex construction installation: a heuristic two-stage resource scheduling optimisation approach. Connect. Sci. Jia Zhao, Wenhao Wang, Liyuan Zhang, Yan Ding
2022	J	`jnl`	A novel in-depth analysis approach for domain-specific problems based on multidomain data. Inf. Sci. Jia Zhao, Yue Zhang, Yan Ding, Qiuye Yu, Ming Hu
2022	J	`jnl`	Explore deep auto-coder and big data learning to hard drive failure prediction: a two-level semi-supervised model. Connect. Sci. Yan Ding, Yunan Zhai, Yujuan Zhai, Jia Zhao
2021	J	`jnl`	Energy-Aware and Deadline-Constrained Task Allocation in Game-Based Mobile Cloud. Int. J. Pattern Recognit. Artif. Intell. Zhuoxi Yang, Yan Ding, Jia Zhao
2021	J	`jnl`	Explore unlabeled big data learning to online failure prediction in safety-aware cloud environment. J. Parallel Distributed Comput. Jia Zhao, Yan Ding, Yunan Zhai, Yuqiang Jiang, Yujuan Zhai, Ming Hu
2019	J	`jnl`	A 'Joint-Me' Task Deployment Strategy for Load Balancing in Edge Computing. IEEE Access Yunmeng Dong, Gaochao Xu, Yan Ding, Xiangyu Meng, Jia Zhao
2019	J	`jnl`	Explore Deep Neural Network and Reinforcement Learning to Large-scale Tasks Processing in Big Data. Int. J. Pattern Recognit. Artif. Intell. Chunyi Wu, Gaochao Xu, Yan Ding, Jia Zhao
2019	C	`conf`	Explore adaptive dropout deep computing and reinforcement learning to large-scale tasks processing for big data. ICCC Jia Zhao, Ming Hu, Yan Ding, Gaochao Xu, Chunyi Wu
2018	J	`jnl`	A Novel Clustering-Based Sampling Approach for Minimum Sample Set in Big Data Environment. Int. J. Pattern Recognit. Artif. Intell. Jia Zhao, Jia Sun, Yunan Zhai, Yan Ding, Chunyi Wu, Ming Hu
2018	J	`jnl`	A novel process-based association rule approach through maximal frequent itemsets for big data processing. Future Gener. Comput. Syst. Zelei Liu, Liang Hu, Chunyi Wu, Yan Ding, Quangang Wen, Jia Zhao
2017	J	`jnl`	A Novel Distributed Recommendation Framework Using Big Data in Social Context. Int. J. Pattern Recognit. Artif. Intell. Gaochao Xu, Yan Ding, Yuqiang Jiang, Ming Hu, Jia Zhao
2017	J	`jnl`	A heuristic placement selection approach of partitions of mobile applications in mobile cloud computing model based on community collaboration. Clust. Comput. Jia Zhao, Shumao Ou, Liang Hu, Yan Ding, Gaochao Xu
2017	J	`jnl`	Explore virtual machine deployment to mobile cloud computing for multi-tenancy and energy conservation in wireless network. Clust. Comput. Yan Ding, Gaochao Xu, Chunyi Wu, Liang Hu, Yunan Zhai, Jia Zhao
2016	J	`jnl`	A Heuristic Clustering-Based Task Deployment Approach for Load Balancing Using Bayes Theorem in Cloud Environment. IEEE Trans. Parallel Distributed Syst. Jia Zhao, Kun Yang, Xiaohui Wei, Yan Ding, Liang Hu, Gaochao Xu
2016	J	`jnl`	A novel trajectory similarity-based approach for location prediction. Int. J. Distributed Sens. Networks Zelei Liu, Liang Hu, Chunyi Wu, Yan Ding, Jia Zhao
2016	—	`conf`	Explore maximal frequent itemsets for big data pre-processing based on small sample in cloud computing. ICUMT Gaochao Xu, Yan Ding, Chunyi Wu, Yunan Zhai, Jia Zhao
2014	J	`jnl`	DSMC: A Novel Distributed Store-Retrieve Approach of Internet Data Using MapReduce Model and Community Detection in Big Data. Int. J. Distributed Sens. Networks Xu Xu, Jia Zhao, Gaochao Xu, Yan Ding, Yunmeng Dong
2013	J	`jnl`	A Survey on Green Computing Based on Cloud Environment. Int. J. Online Eng. Jia Zhao, Liang Hu, Gaochao Xu, Yan Ding, Jianfeng Chu
2013	J	`jnl`	An Approach for Domain Reduction with Data Dependence in Mutation Testing. J. Softw. Gaochao Xu, Yushuang Dong, Xiaodong Fu, Yan Ding, Jia Zhao, Xinzhong Liu
2012	J	`jnl`	A Survey on Data Migration Management in Cloud Environment. J. Digit. Inf. Manag. Liang Hu, Jia Zhao, Gaochao Xu, Yan Ding, Jianfeng Chu

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.