Raeed Al-Sabri

32 papers B 3Journal 25Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	BIAN: Bidirectional interwoven attention network for retinal OCT image classification. J. Vis. Commun. Image Represent. Ahmed Alasri, Zhixiang Chen, Yalong Xiao, Chengzhang Zhu, Abdulrahman Noman, Raeed Al-Sabri, Harrison Xiao Bai
2025	B	`conf`	A Zero-Touch O-RAN Framework for Federated Few-Shot IDS with LLM-Oracle Verification. GLOBECOM Abdullatif Albaseer, Moqbel Hamood, Raeed Al-Sabri, Mohamed M. Abdallah, Ala I. Al-Fuqaha
2025	J	`jnl`	A lightweight deep learning model with knowledge distillation for pulmonary diseases detection in chest X-rays. Multim. Tools Appl. Mohammed A. Asham, Amal A. Al-Shargabi, Raeed Al-Sabri, Ibrahim Meftah
2025	B	`conf`	ADMGNAS: Attention-based Dynamic Multiview Spatiotemporal Graph Neural Architecture Search for Traffic Prediction in Smart City. PIMRC Raeed Al-Sabri, Abdullatif Albaseer, Mohamed M. Abdallah, Ala I. Al-Fuqaha
2025	J	`jnl`	AMSFuse: Adaptive Multi-Scale Feature Fusion Network for Diabetic Retinopathy Classification. Comput. Mater. Continua Chengzhang Zhu, Ahmed Alasri, Tao Xu, Yalong Xiao, Abdulrahman Noman, Raeed Al-Sabri, Xuanchu Duan, Monir Abdullah
2025	J	`jnl`	Asymmetric augmented paradigm-based graph neural architecture search. Inf. Process. Manag. Zhenpeng Wu, Jiamin Chen, Raeed Al-Sabri, Babatounde Moctard Oloulade, Jianliang Gao
2025	J	`jnl`	FEGGNN: Feature-Enhanced Gated Graph Neural Network for robust few-shot skin disease classification. Comput. Biol. Medicine Abdulrahman Noman, Beiji Zou, Chengzhang Zhu, Mohammed Alhabib, Raeed Al-Sabri
2025	J	`jnl`	GCDPL-Net: graph-based co-attention discriminative prototype learning networks for few-shot classification. Int. J. Mach. Learn. Cybern. Mohammed Alhabib, Zuping Zhang, Abdulrahman Noman, Raeed Al-Sabri, Majjed Al-Qatf
2025	J	`jnl`	MGATAF: multi-channel graph attention network with adaptive fusion for cancer-drug response prediction. BMC Bioinform. Dhekra Saeed, Huanlai Xing, Barakat AlBadani, Li Feng, Raeed Al-Sabri, Monir Abdullah, Amir Rehman
2025	B	`conf`	MGCRL: Multi-Scale Graph Contrastive Representation Learning For Network Intrusion Detection. GLOBECOM Raeed Al-Sabri, Abdullatif Albaseer, Mohamed M. Abdallah, Ala I. Al-Fuqaha
2025	J	`jnl`	Shapley-guided pruning for efficient graph neural architecture prediction in distributed learning environments. Inf. Sci. Babatounde Moctard Oloulade, Jianliang Gao, Jiamin Chen, Raeed Al-Sabri, Zhenpeng Wu, Monir Abdullah
2025	—	`conf`	Station-Aware Patch-Gated Temporal Transformer for Multihorizon Forecasting in Smart City Applications. ComComAP Raeed Al-Sabri, Saad Hameed, M. Rami Alfarra, Mohamed M. Abdallah, Ala I. Al-Fuqaha
2025	—	`conf`	Towards Better Graph Anomaly Detection: A Performance-Aware Neural Architecture Search Approach. ICANN (1) Babatounde Moctard Oloulade, Jianliang Gao, Raeed Al-Sabri, Jiamin Chen, Zhenpeng Wu
2024	J	`jnl`	A deep ensemble learning framework for COVID-19 detection in chest X-ray images. Netw. Model. Anal. Health Informatics Bioinform. Sohaib Asif, Qurrat Ul Ain, Muhammad Awais, Kamran Amjad, Omair Bilal, Raeed Al-Sabri, Monir Abdullah
2024	J	`jnl`	Adaptive graph contrastive learning with joint optimization of data augmentation and graph encoder. Knowl. Inf. Syst. Zhenpeng Wu, Jiamin Chen, Raeed Al-Sabri, Babatounde Moctard Oloulade, Jianliang Gao
2024	J	`jnl`	AutoAMS: Automated attention-based multi-modal graph learning architecture search. Neural Networks Raeed Al-Sabri, Jianliang Gao, Jiamin Chen, Babatounde Moctard Oloulade, Zhenpeng Wu
2024	J	`jnl`	AutoDDI: Drug-Drug Interaction Prediction With Automated Graph Neural Network. IEEE J. Biomed. Health Informatics Jianliang Gao, Zhenpeng Wu, Raeed Al-Sabri, Babatounde Moctard Oloulade, Jiamin Chen
2024	J	`jnl`	AutoTGRL: an automatic text-graph representation learning framework. Neural Comput. Appl. Raeed Al-Sabri, Jianliang Gao, Jiamin Chen, Babatounde Moctard Oloulade, Tengfei Lyu
2024	J	`jnl`	CommGNAS: Unsupervised Graph Neural Architecture Search for Community Detection. IEEE Trans. Emerg. Top. Comput. Jianliang Gao, Jiamin Chen, Babatounde Moctard Oloulade, Raeed Al-Sabri, Tengfei Lyu, Ji Zhang, Zhao Li
2024	J	`jnl`	Decoupled differentiable graph neural architecture search. Inf. Sci. Jiamin Chen, Jianliang Gao, Zhenpeng Wu, Raeed Al-Sabri, Babatounde Moctard Oloulade
2024	J	`jnl`	Depth-adaptive graph neural architecture search for graph classification. Knowl. Based Syst. Zhenpeng Wu, Jiamin Chen, Raeed Al-Sabri, Babatounde Moctard Oloulade, Jianliang Gao
2024	J	`jnl`	Graph neural architecture prediction. Knowl. Inf. Syst. Jianliang Gao, Babatounde Moctard Oloulade, Raeed Al-Sabri, Jiamin Chen, Tengfei Lyu, Zhenpeng Wu
2024	J	`jnl`	LitefusionNet: Boosting the performance for medical image classification with an intelligent and lightweight feature fusion network. J. Comput. Sci. Sohaib Asif, Qurrat Ul Ain, Raeed Al-Sabri, Monir Abdullah
2024	—	`conf`	M3GNAS: Multi-modal Multi-view Graph Neural Architecture Search for Medical Outcome Predictions. BIBM Raeed Al-Sabri, Jianliang Gao, Jiamin Chen, Babatounde Moctard Oloulade, Zhenpeng Wu, Monir Abdullah, Xiaohua Hu
2023	J	`jnl`	Cancer drug response prediction with surrogate modeling-based graph neural architecture search. Bioinform. Babatounde Moctard Oloulade, Jianliang Gao, Jiamin Chen, Raeed Al-Sabri, Zhenpeng Wu
2023	J	`jnl`	GM2NAS: multitask multiview graph neural architecture search. Knowl. Inf. Syst. Jianliang Gao, Raeed Al-Sabri, Babatounde Moctard Oloulade, Jiamin Chen, Tengfei Lyu, Zhenpeng Wu
2023	J	`jnl`	Multi-View Graph Neural Architecture Search for Biomedical Entity and Relation Extraction. IEEE ACM Trans. Comput. Biol. Bioinform. Raeed Al-Sabri, Jianliang Gao, Jiamin Chen, Babatounde Moctard Oloulade, Tengfei Lyu
2023	J	`jnl`	Neural predictor-based automated graph classifier framework. Mach. Learn. Babatounde Moctard Oloulade, Jianliang Gao, Jiamin Chen, Raeed Al-Sabri, Tengfei Lyu
2023	J	`jnl`	SMGNN: span-to-span multi-channel graph neural network for aspect-sentiment triplet extraction. J. Intell. Inf. Syst. Barakat AlBadani, Jian Dong, Ronghua Shi, Raeed Al-Sabri, Dhekra Saeed, Alaa Thobhani
2022	J	`jnl`	A Principal Neighborhood Aggregation-Based Graph Convolutional Network for Pneumonia Detection. Sensors Akram Ali Ali Guail, Jinsong Gui, Babatounde Moctard Oloulade, Raeed Al-Sabri
2021	—	`conf`	LAMAD: A Linguistic Attentional Model for Arabic Text Diacritization. EMNLP (Findings) Raeed Al-Sabri, Jianliang Gao
2020	J	`jnl`	The Impact of Weighting Schemes and Stemming Process on Topic Modeling of Arabic Long and Short Texts. ACM Trans. Asian Low Resour. Lang. Inf. Process. Tinghuai Ma, Raeed Al-Sabri, Lejun Zhang, Bockarie Daniel Marah, Najla Al-Nabhan

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.