Zengpeng Li - RankMe

14 papers Journal 14

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	ConoDL: a deep learning framework for rapid generation and prediction of conotoxins. J. Comput. Aided Mol. Des. Menghan Guo, Zengpeng Li, Xuejin Deng, Ding Luo, Jingyi Yang, Yingjun Chen, Weiwei Xue
2025	J	`jnl`	Energy, Cost and Reliability-Aware Workflow Scheduling on Multi-Cloud Systems: A Multi-Objective Evolutionary Approach. IEEE Trans. Netw. Serv. Manag. Zhuoyue Fang, Huiqun Yu, Guisheng Fan, Zengpeng Li, Jiayin Zhang
2024	J	`jnl`	Adaptive edge service deployment in burst load scenarios using deep reinforcement learning. J. Supercomput. Jin Xu, Huiqun Yu, Guisheng Fan, Jiayin Zhang, Zengpeng Li, Qifeng Tang
2024	J	`jnl`	Cold-Start-Aware Cloud-Native Parallel Service Function Chain Caching in Edge-Cloud Network. IEEE Internet Things J. Jiayin Zhang, Huiqun Yu, Guisheng Fan, Qifeng Tang, Zengpeng Li, Jin Xu
2024	J	`jnl`	Elastic Task Offloading and Resource Allocation Over Hybrid Cloud: A Reinforcement Learning Approach. IEEE Trans. Netw. Serv. Manag. Jiayin Zhang, Huiqun Yu, Guisheng Fan, Zengpeng Li
2024	J	`jnl`	Energy-efficient offloading for DNN-based applications in edge-cloud computing: A hybrid chaotic evolutionary approach. J. Parallel Distributed Comput. Zengpeng Li, Huiqun Yu, Guisheng Fan, Jiayin Zhang, Jin Xu
2024	J	`jnl`	Energy-efficient reliability-aware offloading for delay-sensitive tasks in collaborative edge computing. Concurr. Comput. Pract. Exp. Zengpeng Li, Huiqun Yu, Guisheng Fan, Jiayin Zhang, Jin Xu
2024	J	`jnl`	Handling hierarchy in cloud data centers: A Hyper-Heuristic approach for resource contention and energy-aware Virtual Machine management. Expert Syst. Appl. Jiayin Zhang, Huiqun Yu, Guisheng Fan, Zengpeng Li, Jin Xu, Jun Li
2023	J	`jnl`	An Energy-Efficient Dynamic Scheduling Method of Deadline-Constrained Workflows in a Cloud Environment. IEEE Trans. Netw. Serv. Manag. Guisheng Fan, Xingpeng Chen, Zengpeng Li, Huiqun Yu, Yingxue Zhang
2023	J	`jnl`	Cost-Efficient Fault-Tolerant Workflow Scheduling for Deadline-Constrained Microservice-Based Applications in Clouds. IEEE Trans. Netw. Serv. Manag. Zengpeng Li, Huiqun Yu, Guisheng Fan, Jiayin Zhang
2023	J	`jnl`	Cost-effective approaches for deadline-constrained workflow scheduling in clouds. J. Supercomput. Zengpeng Li, Huiqun Yu, Guisheng Fan
2023	J	`jnl`	Cost-efficient security-aware scheduling for dependent tasks with endpoint contention in edge computing. Comput. Commun. Zengpeng Li, Huiqun Yu, Guisheng Fan, Qifeng Tang, Jiayin Zhang, Liqiong Chen
2022	J	`jnl`	Cold-start aware cloud-native service function chain caching in resource-constrained edge: A reinforcement learning approach. Comput. Commun. Jiayin Zhang, Huiqun Yu, Guisheng Fan, Zengpeng Li
2022	J	`jnl`	Time-cost efficient memory configuration for serverless workflow applications. Concurr. Comput. Pract. Exp. Zengpeng Li, Huiqun Yu, Guisheng Fan

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.