Zexi Tan - RankMe

14 papers A* 1Journal 12Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	HMVI: Unifying Heterogeneous Attributes with Natural Neighbors for Missing Value Inference. CoRR Xiaopeng Luo, Zexi Tan, Zhuowei Wang
2026	J	`jnl`	Hierarchical Reference Sets for Robust Unsupervised Detection of Scattered and Clustered Outliers. CoRR Yiqun Zhang, Zexi Tan, Xiaopeng Luo, Yunlin Liu
2026	J	`jnl`	Hierarchical Reference Sets for Robust Unsupervised Detection of Scattered and Clustered Outliers. IEEE Internet Things J. Yiqun Zhang, Zexi Tan, Xiaopeng Luo, Yunlin Liu
2026	A*	`conf`	Mask the Redundancy: Evolving Masking Representation Learning for Multivariate Time-Series Clustering. AAAI Zexi Tan, Xiaopeng Luo, Yunlin Liu, Yiqun Zhang
2026	J	`jnl`	TFEC: Multivariate Time-Series Clustering via Temporal-Frequency Enhanced Contrastive Learning. CoRR Zexi Tan, Tao Xie, Haoyi Xiao, Baoyao Yang, Yuzhu Ji, An Zeng, Xiang Zhang, Yiqun Zhang
2025	—	`conf`	DE3S: Dual-Enhanced Soft-Sparse Shape Learning for Medical Early Time Series Classification. BIBM Tao Xie, Zexi Tan, Haoyi Xiao, Binbin Sun, Yiqun Zhang
2025	J	`jnl`	DE3S: Dual-Enhanced Soft-Sparse-Shape Learning for Medical Early Time-Series Classification. CoRR Tao Xie, Zexi Tan, Haoyi Xiao, Binbin Sun, Yiqun Zhang
2025	J	`jnl`	Efficient streaming data clustering guided by self-refined organizing map. Int. J. Wavelets Multiresolution Inf. Process. Mei Yin, Zexi Tan, Yunfan Zhang, Yiqun Zhang, Yang Lu
2025	J	`jnl`	Learning Self-Growth Maps for Fast and Accurate Imbalanced Streaming Data Clustering. IEEE Trans. Neural Networks Learn. Syst. Yiqun Zhang, Sen Feng, Pengkai Wang, Zexi Tan, Xiaopeng Luo, Yuzhu Ji, Rong Zou, Yiu-ming Cheung
2025	J	`jnl`	MEET-Sepsis: Multi-Endogenous-View Enhanced Time-Series Representation Learning for Early Sepsis Prediction. CoRR Zexi Tan, Tao Xie, Binbin Sun, Xiang Zhang, Yiqun Zhang, Yiu-ming Cheung
2025	J	`jnl`	Mask the Redundancy: Evolving Masking Representation Learning for Multivariate Time-Series Clustering. CoRR Zexi Tan, Xiaopeng Luo, Yunlin Liu, Yiqun Zhang
2025	J	`jnl`	SDENK: Unbiased subspace density-k-clustering. Neurocomputing Rong Zou, Yunfan Zhang, Mingjie Zhao, Zexi Tan, Yiqun Zhang, Yiu-ming Cheung
2025	J	`jnl`	Towards Clustering of Incomplete Mixed-Attribute Data. Expert Syst. J. Knowl. Eng. Chuyao Zhang, Xinxi Chen, Zexi Tan, Fangqing Gu, Yuzhu Ji, Yiqun Zhang
2019	J	`jnl`	BrainEXP: a database featuring with spatiotemporal expression variations and co-expression organizations in human brains. Bioinform. Chuan Jiao, Pengpeng Yan, Cuihua Xia, Zhaoming Shen, Zexi Tan, Yanyan Tan, Kangli Wang, Yi Jiang, Lingling Huang, Rujia Dai, Yu Wei, Yan Xia, Qingtuan Meng, Yanmei Ouyang, Liu Yi, Fangyuan Duan, Jiacheng Dai, Shunan Zhao, Chunyu Liu, Chao Chen

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.