Yangtao Zhou - RankMe

13 papers A* 1A 4Misc 1Journal 6Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	A	`conf`	A Spectral Heterogeneous Diffusion Framework for Knowledge-aware Recommendation. WSDM Xiangming Li, Hua Chu, Chengyu Feng, Jianan Li, Yangtao Zhou, Qingshan Li, Wanqiang Yang
2026	J	`jnl`	Knowledge-guided course recommendation in MOOCs with cross-graph and forgetting-aware cross-attention. Appl. Soft Comput. Yangtao Zhou, Qingshan Li, Ruoyu Li, Hua Chu, Jianan Li, Feifei Zhu, Xiangming Li, Chengyu Feng, Wanqiang Yang
2026	J	`jnl`	Plang: Efficient prompt engineering language for blending natural language and control flow in large language models. Expert Syst. Appl. Jingzhao Hu, Wenjing Bi, Yangtao Zhou, Jiahui Zheng, Shuai Zhang, Hua Chu, Lu Wang, Qingshan Li
2025	A	`conf`	Breaking Knowledge Boundaries: Cognitive Distillation-enhanced Cross-Behavior Course Recommendation Model. RecSys Ruoyu Li, Yangtao Zhou, Chenzhang Li, Hua Chu, Jianan Li, Yuhan Bian
2025	A	`conf`	Building Bridges, Not Walls: Fairness-Aware and Accurate Recommendation of Code Reviewers via LLm-Based Agents Collaboration. ICPC Luqiao Wang, Qingshan Li, Di Cui, Mingkang Wang, Yutong Zhao, Yongye Xu, Huiying Zhuang, Yangtao Zhou, Lu Wang
2025	J	`jnl`	CoCoDiff: Diversifying Skeleton Action Features via Coarse-Fine Text-Co-Guided Latent Diffusion. CoRR Zhifu Zhao, Xian-Hua Han, Jianan Li, Shaoxin Wu, Fu Li, Yangtao Zhou, Yang Li
2025	A	`conf`	DeMBR: Denoising Model with Memory Pruning and Semantic Guidance for Multi-Behavior Recommendation. WSDM Shuai Zhang, Hua Chu, Jianan Li, Yangtao Zhou, Shirong Wang, Qiaofei Sun
2025	J	`jnl`	Diffusion-driven SpatioTemporal Graph KANsformer for Medical Examination Recommendation. CoRR Jianan Li, Yangtao Zhou, Zhifu Zhao, Qinglan Huang, Jian Qi, Xiao He, Hua Chu, Fu Li
2025	Misc	`conf`	Dual Multi-Scale GCN with Deformable Temporal Kernel for Skeleton-based Action Recognition. ICASSP Jianan Li, Yangtao Zhou, Hua Chu, Han Wang, Zhifu Zhao, Fei Li, Qingshan Li
2025	J	`jnl`	Dual-tower model with semantic perception and timespan-coupled hypergraph for next-basket recommendation. Neural Networks Yangtao Zhou, Hua Chu, Qingshan Li, Jianan Li, Shuai Zhang, Feifei Zhu, Jingzhao Hu, Luqiao Wang, Wanqiang Yang
2025	J	`jnl`	Spatiotemporal-view member preference contrastive representation learning for group recommendation. Mach. Learn. Yangtao Zhou, Qingshan Li, Hua Chu, Jianan Li, Biaobiao Wei, Shuai Zhang, Jialong Han
2024	—	`conf`	DIDA: Dynamic Individual-to-integrateD Augmentation for Self-supervised Skeleton-Based Action Recognition. PRCV (7) Haobo Huang, Jianan Li, Hongbin Fan, Zhifu Zhao, Yangtao Zhou
2024	A*	`conf`	Unity Is Strength: Collaborative LLM-Based Agents for Code Reviewer Recommendation. ASE Luqiao Wang, Yangtao Zhou, Huiying Zhuang, Qingshan Li, Di Cui, Yutong Zhao, Lu Wang

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.