Emadeldeen Eldele

40 papers A* 7Journal 32Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	A Unified Shape-Aware Foundation Model for Time Series Classification. AAAI Zhen Liu, Yucheng Wang, Boyuan Li, Junhao Zheng, Emadeldeen Eldele, Min Wu, Qianli Ma
2026	J	`jnl`	A Unified Shape-Aware Foundation Model for Time Series Classification. CoRR Zhen Liu, Yucheng Wang, Boyuan Li, Junhao Zheng, Emadeldeen Eldele, Min Wu, Qianli Ma
2026	J	`jnl`	Evidentially Calibrated Source-Free Time-Series Domain Adaptation With Temporal Imputation. IEEE Trans. Knowl. Data Eng. Mohamed Ragab, Peiliang Gong, Emadeldeen Eldele, Wenyu Zhang, Min Wu, Chuan-Sheng Foo, Daoqiang Zhang, Xiaoli Li, Zhenghua Chen
2026	J	`jnl`	MSA-CNN: A lightweight multi-scale CNN with attention for sleep stage classification. Biomed. Signal Process. Control. Stephan Goerttler, Yucheng Wang, Emadeldeen Eldele, Fei He, Min Wu
2026	J	`jnl`	Time Series Domain Adaptation via Latent Invariant Causal Mechanism. IEEE Trans. Pattern Anal. Mach. Intell. Ruichu Cai, Junxian Huang, Zhenhui Yang, Zijian Li, Emadeldeen Eldele, Min Wu, Fuchun Sun
2025	J	`jnl`	Adapting LLMs to Time Series Forecasting via Temporal Heterogeneity Modeling and Semantic Alignment. CoRR Yanru Sun, Emadeldeen Eldele, Zongxia Xie, Yucheng Wang, Wenzhe Niu, Qinghua Hu, Chee Keong Kwoh, Min Wu
2025	J	`jnl`	Bridging Distribution Gaps in Time Series Foundation Model Pretraining with Prototype-Guided Normalization. CoRR Peiliang Gong, Emadeldeen Eldele, Min Wu, Zhenghua Chen, Xiao-Li Li, Daoqiang Zhang
2025	A*	`conf`	Counterfactual Contrastive Learning with Normalizing Flows for Robust Treatment Effect Estimation. ICML Jiaxuan Zhang, Emadeldeen Eldele, Fuyuan Cao, Yang Wang, Xiaoli Li, Jiye Liang
2025	J	`jnl`	EntroPE: Entropy-Guided Dynamic Patch Encoder for Time Series Forecasting. CoRR Sachith Abeywickrama, Emadeldeen Eldele, Min Wu, Xiaoli Li, Chau Yuen
2025	A*	`conf`	Hierarchical Classification Auxiliary Network for Time Series Forecasting. AAAI Yanru Sun, Zongxia Xie, Dongyue Chen, Emadeldeen Eldele, Qinghua Hu
2025	A*	`conf`	Learning Soft Sparse Shapes for Efficient Time-Series Classification. ICML Zhen Liu, Yicheng Luo, Boyuan Li, Emadeldeen Eldele, Min Wu, Qianli Ma
2025	J	`jnl`	Learning Soft Sparse Shapes for Efficient Time-Series Classification. CoRR Zhen Liu, Yicheng Luo, Boyuan Li, Emadeldeen Eldele, Min Wu, Qianli Ma
2025	J	`jnl`	MSA-CNN: A Lightweight Multi-Scale CNN with Attention for Sleep Stage Classification. CoRR Stephan Goerttler, Yucheng Wang, Emadeldeen Eldele, Min Wu, Fei He
2025	J	`jnl`	Time Series Domain Adaptation via Latent Invariant Causal Mechanism. CoRR Ruichu Cai, Junxian Huang, Zhenhui Yang, Zijian Li, Emadeldeen Eldele, Min Wu, Fuchun Sun
2025	J	`jnl`	UniFault: A Fault Diagnosis Foundation Model from Bearing Data. CoRR Emadeldeen Eldele, Mohamed Ragab, Xu Qing, Edward, Zhenghua Chen, Min Wu, Xiaoli Li, Jay Lee
2024	—	`conf`	Bi-hemisphere Interaction Convolutional Neural Network for Motor Imagery Classification. EMBC Xiaohao Lin, Emadeldeen Eldele, Zhenghua Chen, Min Wu, Han Wei Ng, Cuntai Guan
2024	J	`jnl`	Contrastive Domain Adaptation for Time-Series Via Temporal Mixup. IEEE Trans. Artif. Intell. Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li
2024	J	`jnl`	ECGTransForm: Empowering adaptive ECG arrhythmia classification framework with bidirectional transformer. Biomed. Signal Process. Control. Hany A. El-Ghaish, Emadeldeen Eldele
2024	J	`jnl`	Evidentially Calibrated Source-Free Time-Series Domain Adaptation with Temporal Imputation. CoRR Mohamed Ragab, Peiliang Gong, Emadeldeen Eldele, Wenyu Zhang, Min Wu, Chuan-Sheng Foo, Daoqiang Zhang, Xiaoli Li, Zhenghua Chen
2024	J	`jnl`	Hierarchical Classification Auxiliary Network for Time Series Forecasting. CoRR Yanru Sun, Zongxia Xie, Dongyue Chen, Emadeldeen Eldele, Qinghua Hu
2024	J	`jnl`	Label-Efficient Time Series Representation Learning: A Review. IEEE Trans. Artif. Intell. Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiao-Li Li
2024	J	`jnl`	Learning Pattern-Specific Experts for Time Series Forecasting Under Patch-level Distribution Shift. CoRR Yanru Sun, Zongxia Xie, Emadeldeen Eldele, Dongyue Chen, Qinghua Hu, Min Wu
2024	J	`jnl`	Self-Supervised Autoregressive Domain Adaptation for Time Series Data. IEEE Trans. Neural Networks Learn. Syst. Mohamed Ragab, Emadeldeen Eldele, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li
2024	A*	`conf`	TSLANet: Rethinking Transformers for Time Series Representation Learning. ICML Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Xiaoli Li
2024	J	`jnl`	TSLANet: Rethinking Transformers for Time Series Representation Learning. CoRR Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Xiaoli Li
2023	J	`jnl`	ADAST: Attentive Cross-Domain EEG-Based Sleep Staging Framework With Iterative Self-Training. IEEE Trans. Emerg. Top. Comput. Intell. Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li, Cuntai Guan
2023	J	`jnl`	ADATIME: A Benchmarking Suite for Domain Adaptation on Time Series Data. ACM Trans. Knowl. Discov. Data Mohamed Ragab, Emadeldeen Eldele, Wee Ling Tan, Chuan-Sheng Foo, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li
2023	J	`jnl`	Label-efficient Time Series Representation Learning: A Review. CoRR Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li
2023	J	`jnl`	Self-Supervised Contrastive Representation Learning for Semi-Supervised Time-Series Classification. IEEE Trans. Pattern Anal. Mach. Intell. Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li, Cuntai Guan
2023	A*	`conf`	Source-Free Domain Adaptation with Temporal Imputation for Time Series Data. KDD Mohamed Ragab, Emadeldeen Eldele, Min Wu, Chuan-Sheng Foo, Xiaoli Li, Zhenghua Chen
2023	J	`jnl`	Source-Free Domain Adaptation with Temporal Imputation for Time Series Data. CoRR Mohamed Ragab, Emadeldeen Eldele, Min Wu, Chuan-Sheng Foo, Xiaoli Li, Zhenghua Chen
2022	J	`jnl`	ADATIME: A Benchmarking Suite for Domain Adaptation on Time Series Data. CoRR Mohamed Ragab, Emadeldeen Eldele, Wee Ling Tan, Chuan-Sheng Foo, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li
2022	J	`jnl`	CoTMix: Contrastive Domain Adaptation for Time-Series via Temporal Mixup. CoRR Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li
2022	J	`jnl`	Conditional Contrastive Domain Generalization for Fault Diagnosis. IEEE Trans. Instrum. Meas. Mohamed Ragab, Zhenghua Chen, Wenyu Zhang, Emadeldeen Eldele, Min Wu, Chee Keong Kwoh, Xiaoli Li
2022	J	`jnl`	Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification. CoRR Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li, Cuntai Guan
2022	J	`jnl`	Self-supervised Learning for Label-Efficient Sleep Stage Classification: A Comprehensive Evaluation. CoRR Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li
2021	J	`jnl`	Adversarial Domain Adaptation with Self-Training for EEG-based Sleep Stage Classification. CoRR Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li, Cuntai Guan
2021	J	`jnl`	Self-supervised Autoregressive Domain Adaptation for Time Series Data. CoRR Mohamed Ragab, Emadeldeen Eldele, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li
2021	A*	`conf`	Time-Series Representation Learning via Temporal and Contextual Contrasting. IJCAI Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li, Cuntai Guan
2021	J	`jnl`	Time-Series Representation Learning via Temporal and Contextual Contrasting. CoRR Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li, Cuntai Guan

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.