Zehua Ren

13 papers C 1Journal 5Unranked 7
YearRankTypeTitle / Venue / Authors
2026 J jnl
A Segmentation-Driven Editing Method for Bolt Defect Augmentation and Detection.
IEEE Trans. Syst. Man Cybern. Syst.
Yangjie Xiao, Ke Zhang, Jiacun Wang, Xin Sheng, Yurong Guo, Meijuan Chen, Zehua Ren, Zhaoye Zheng, Zhenbing Zhao
2025 J jnl
A Segmentation-driven Editing Method for Bolt Defect Augmentation and Detection.
CoRR
Yangjie Xiao, Ke Zhang, Jiacun Wang, Xin Sheng, Yurong Guo, Meijuan Chen, Zehua Ren, Zhaoye Zheng, Zhenbing Zhao
2025 J jnl
BioDiag-Net: Dynamic Multisite Graph Convolutional Network for Computer-Aided ASD Diagnosis with Biomarker Visualization.
Inf. Technol. Control.
Bo Yu, Yue Li, Zehua Ren, Jingqi Pan
2025 — conf
Flexibly Distilled 3D Rectified Flow with Anatomical Constraints for Developmental Infant Brain MRI Prediction.
MICCAI (15)
Haifeng Wang, Zehua Ren, Heng Chang, Xinmei Qiu, Fan Wang, Chunfeng Lian, Jianhua Ma
2025 J jnl
HyperLAC: Hypergraph-based Large-scale Alert Classification with spatial-temporal context enhancement.
Knowl. Based Syst.
Shilong Zhang, Zian Luo, Zehua Ren, Yumeng Zhu, Haichuan Zhang, Yang Liu
2024 — conf
Controllable Counterfactual Generation for Interpretable Medical Image Classification.
MICCAI (10)
Shiyu Liu, Fan Wang, Zehua Ren, Chunfeng Lian, Jianhua Ma
2024 — conf
MNSSA: Meso-level Network Security Situation Awareness for ICS via Graph Evolution Analysis.
CASE
Shilong Zhang, Hui Zhang, Guo Chen, He Luo, Meiqi Wu, Hongxiang Chen, Zehua Ren, Zijun Wang, Yang Liu
2024 C conf
Mechanism Analysis of the Instability in Series Hybrid Electric Powertrain.
INDIN
Wei Liu, Chao Yang, Zehua Ren, Sibo Kan
2023 — conf
Punctate White Matter Lesion Segmentation in Preterm Infants Powered by Counterfactually Generative Learning.
MICCAI (5)
Zehua Ren, Yongheng Sun, Miaomiao Wang, Yuying Feng, Xianjun Li, Chao Jin, Jian Yang, Chunfeng Lian, Fan Wang
2023 J jnl
Punctate White Matter Lesion Segmentation in Preterm Infants Powered by Counterfactually Generative Learning.
CoRR
Zehua Ren, Yongheng Sun, Miaomiao Wang, Yuying Feng, Xianjun Li, Chao Jin, Jian Yang, Chunfeng Lian, Fan Wang
2022 — conf
An Enhanced EWMA for Alert Reduction and Situation Awareness in Industrial Control Networks
CASE
Baoxiang Jiang, Yang Liu, Huixiang Liu, Zehua Ren, Yun Wang, Yuanyi Bao, Wenqing Wang
2022 — conf
Network Security Situation Awareness Based on Spatio-temporal Correlation of Alarms.
INFOCOM Workshops
Zehua Ren, Yang Liu, Huixiang Liu, Baoxiang Jiang, Xiangzhen Yao, Lin Li, Haiwen Yang, Ting Liu
2022 — conf
Predicting Passenger Flow in Hangzhou Metro Stations - Using a Time Series ARIMA Model based on Desensitized Data.
ICCSIE
Zehong Ren, Hongzhou Gu, Zehua Ren

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.