Lei Liu

15 papers Journal 14Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Behavioral Decision-Making Model of Learning and Memory for Mobile Robot Triggered by Curiosity. IEEE Trans. Cogn. Dev. Syst. Dongshu Wang, Qi Liu, Xulin Gao, Lei Liu
2024	J	`jnl`	Exploring unknown environments: motivated developmental learning for autonomous navigation of mobile robots. Intell. Serv. Robotics Yuyang Zhou, Dongshu Wang, Lei Liu
2024	J	`jnl`	Integrated model of cerebellal supervised learning and basal ganglia's reinforcement learning for mobile robot behavioral decision-making. Cogn. Syst. Res. Zhiqiang Wu, Dongshu Wang, Lei Liu
2024	J	`jnl`	Neuromodulatory developmental learning of the mobile robots corresponding to the unexpected obstacles. Cogn. Syst. Res. Hongyan Zhao, Dongshu Wang, Lei Liu
2022	J	`jnl`	An Incremental Learning Model for Mobile Robot: From Short-Term Memory to Long-Term Memory. IEEE Trans. Artif. Intell. Dongshu Wang, Kai Yang, Lei Liu, Heshan Wang
2022	J	`jnl`	Behavior Decision of Mobile Robot With a Neurophysiologically Motivated Reinforcement Learning Model. IEEE Trans. Cogn. Dev. Syst. Dongshu Wang, Shuli Chen, Yuhang Hu, Lei Liu, Heshan Wang
2021	J	`jnl`	An adaptive behavior decision model of mobile robot based on the neuromodulation. Artif. Life Robotics Dongshu Wang, Kai Yang, Lei Liu
2021	J	`jnl`	Behavioral Decision-Making of Mobile Robot in Unknown Environment with the Cognitive Transfer. J. Intell. Robotic Syst. Dongshu Wang, Kai Yang, Heshan Wang, Lei Liu
2021	J	`jnl`	Path planning of mobile robot in dynamic environment: fuzzy artificial potential field and extensible neural network. Artif. Life Robotics Dongshu Wang, Shuli Chen, Yadong Zhang, Lei Liu
2018	J	`jnl`	Developmental Network: An Internal Emergent Object Feature Learning. Neural Process. Lett. Dongshu Wang, Junhao Wang, Lei Liu
2018	J	`jnl`	Emergent face orientation recognition with internal neurons of the developmental network. Prog. Artif. Intell. Dongshu Wang, Hui Shan, Yuan Tian, Lei Liu
2018	—	`conf`	Goal-Directed Behavior Control Based on the Mechanism of Neuromodulation. BICS Dongshu Wang, Hui Shan, Lei Liu
2018	J	`jnl`	Particle swarm optimization algorithm: an overview. Soft Comput. Dongshu Wang, Dapei Tan, Lei Liu
2017	J	`jnl`	How internal neurons represent the short context: an emergent perspective. Prog. Artif. Intell. Dongshu Wang, Jiaming Chen, Lei Liu
2016	J	`jnl`	Unknown environment exploration of multi-robot system with the FORDPSO. Swarm Evol. Comput. Dongshu Wang, Haitao Wang, Lei 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.