Zeyu Guo - RankMe

11 papers A* 1Journal 7Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	An area/energy-efficient RRAM computing-in-memory macro with fully-charge-domain multi-bit computation. Sci. China Inf. Sci. Zhi Li, Shengzhe Yan, Jun Wang, Zhuoyu Dai, Zeyu Guo, Zhaori Cong, Zhihang Qian, Xiangqu Fu, Xu Zheng, Chunmeng Dou, Dashan Shang, Jinshan Yue
2025	J	`jnl`	A High-Density Energy-Efficient CNM Macro Using Hybrid RRAM and SRAM for Memory-Bound Applications. IEEE Trans. Very Large Scale Integr. Syst. Jun Wang, Shengzhe Yan, Xiangqu Fu, Zhihang Qian, Zhi Li, Zeyu Guo, Zhuoyu Dai, Zhaori Cong, Chunmeng Dou, Feng Zhang, Jinshan Yue, Dashan Shang
2025	J	`jnl`	A monolithic 3D IGZO-RRAM-SRAM-integrated architecture for robust and efficient compute-in-memory enabling equivalent-ideal device metrics. Sci. China Inf. Sci. Shengzhe Yan, Zhaori Cong, Zi Wang, Zhuoyu Dai, Zeyu Guo, Zhihang Qian, Xufan Li, Xu Zheng, Chuanke Chen, Nianduan Lu, Chunmeng Dou, Guanhua Yang, Xiaoxin Xu, Di Geng, Jinshan Yue, Lingfei Wang, Ling Li, Ming Liu
2025	J	`jnl`	An RRAM-Based Computing-in-Memory Macro With Low-Power Readout/Hold Circuits and Activation Differential Strategy for AdderNet. IEEE Trans. Very Large Scale Integr. Syst. Zhihang Qian, Shengzhe Yan, Zhuoyu Dai, Zeyu Guo, Zhaori Cong, Yifan He, Chunmeng Dou, Feng Zhang, Jinshan Yue, Yongpan Liu
2024	—	`conf`	A 41.7TOPS/W@INT8 Computing-in-Memory Processor with Zig-Zag Backbone-Systolic CIM and Block/Self-Gating CAM for NN/Recommendation Applications. VLSI Technology and Circuits Zhuoyu Dai, Shengzhe Yan, Zhaori Cong, Zeyu Guo, Yifan He, Wenyu Sun, Chunmeng Dou, Feng Zhang, Jinshan Yue, Yongpan Liu, Ming Liu
2024	A*	`conf`	IG-CRM: Area/Energy-Efficient IGZO-Based Circuits and Architecture Design for Reconfigurable CIM/CAM Applications. DAC Zeyu Guo, Jinshan Yue, Shengzhe Yan, Zhuoyu Dai, Xiangqu Fu, Zhaori Cong, Zening Niu, Ke Hu, Lihua Xu, Jiawei Wang, Lingfei Wang, Guanhua Yang, Di Geng, Ling Li
2023	J	`jnl`	An ADC-Less RRAM-Based Computing-in-Memory Macro With Binary CNN for Efficient Edge AI. IEEE Trans. Circuits Syst. II Express Briefs Yi Li, Jia Chen, Linfang Wang, Woyu Zhang, Zeyu Guo, Jun Wang, Yongkang Han, Zhi Li, Fei Wang, Chunmeng Dou, Xiaoxin Xu, Jianguo Yang, Zhongrui Wang, Dashan Shang
2022	—	`conf`	3D Reservoir Computing with High Area Efficiency (5.12 TOPS/mm VLSI Technology and Circuits Wenxuan Sun, Woyu Zhang, Jie Yu, Yi Li, Zeyu Guo, Jinru Lai, Danian Dong, Xu Zheng, Fei Wang, Shaoyang Fan, Xiaoxin Xu, Dashan Shang, Ming Liu
2022	—	`conf`	Few-shot graph learning with robust and energy-efficient memory-augmented graph neural network (MAGNN) based on homogeneous computing-in-memory. VLSI Technology and Circuits Woyu Zhang, Shaocong Wang, Yi Li, Xiaoxin Xu, Danian Dong, Nanjia Jiang, Fei Wang, Zeyu Guo, Renrui Fang, Chunmeng Dou, Kai Ni, Zhongrui Wang, Dashan Shang, Ming Liu
2022	J	`jnl`	Mixed-Precision Continual Learning Based on Computational Resistance Random Access Memory. Adv. Intell. Syst. Yi Li, Woyu Zhang, Xiaoxin Xu, Yifan He, Danian Dong, Nanjia Jiang, Fei Wang, Zeyu Guo, Shaocong Wang, Chunmeng Dou, Yongpan Liu, Zhongrui Wang, Dashan Shang
2022	J	`jnl`	Mixed-Precision Continual Learning Based on Computational Resistance Random Access Memory. Adv. Intell. Syst. Yi Li, Woyu Zhang, Xiaoxin Xu, Yifan He, Danian Dong, Nanjia Jiang, Fei Wang, Zeyu Guo, Shaocong Wang, Chunmeng Dou, Yongpan Liu, Zhongrui Wang, Dashan Shang

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.