| 2026 | KDD | Breaking the Boundary Barrier: Robust Model Fingerprinting via Unlearnable Examples in Model-Parameter Space. | Tianlong Xu, Zixiong Wang, Gaoyang Liu, Jian Chen, Ahmed M. Abdelmoniem, Chen Wang |
| 2026 | Mobisys | FedORA: Federated Objective-Resolved Adaptation for Non-Stationary Environments. | Wai Fong Tam, Songyuan Li, Ahmed M. Abdelmoniem |
| 2025 | CCS | Prototype Surgery: Tailoring Neural Prototypes via Soft Labels for Efficient Machine Unlearning. | Gaoyang Liu, Xijie Wang, Zixiong Wang, Chen Wang, Ahmed M. Abdelmoniem, Desheng Wang |
| 2025 | ECAI | Discovering Latent Knowledge Prototypes for Heterogeneous Federated Learning. | Qilei Li, Ahmed M. Abdelmoniem |
| 2025 | HPCC | Split Fine-Tuning of BERT-Based Music Models in the Edge-Cloud Continuum: An Empirical Analysis. | Bradley Aldous, Ahmed M. Abdelmoniem |
| 2025 | ICLR | Query-based Knowledge Transfer for Heterogeneous Learning Environments. | Norah Alballa, Wenxuan Zhang, Ziquan Liu, Ahmed M. Abdelmoniem, Mohamed Elhoseiny, Marco Canini |
| 2025 | IJCNN | Hierarchical Knowledge Structuring for Effective Federated Learning in Heterogeneous Environments. | Wai Fong Tam, Qilei Li, Ahmed M. Abdelmoniem |
| 2025 | INFOCOM | CASH: Class-aware AQM via in-Switch Hysteresis Control for Data Center Networks. | Waheed G. Gadallah, Brahim Bensaou, Ahmed M. Abdelmoniem |
| 2025 | KDD | From Expansion to Retraction: Long-tailed Machine Unlearning via Boundary Manipulation. | Min Chen, Weizhuo Gao, Chen Wang, Gaoyang Liu, Ahmed M. Abdelmoniem, Kai Peng |
| 2024 | EuroSys | FLOAT: Federated Learning Optimizations with Automated Tuning. | Ahmad Faraz Khan, Azal Ahmad Khan, Ahmed M. Abdelmoniem, Samuel Fountain, Ali Raza Butt, Ali Anwar |
| 2024 | ICWSM | Decentralised Moderation for Interoperable Social Networks: A Conversation-Based Approach for Pleroma and the Fediverse. | Vibhor Agarwal, Aravindh Raman, Nishanth Sastry, Ahmed M. Abdelmoniem, Gareth Tyson, Ignacio Castro |
| 2024 | QRS | Performance Profiling of Federated Learning Across Heterogeneous Mobile Devices. | Jos A. Esquivel, Bradley Aldous, Ahmed M. Abdelmoniem, Ahmad Alhilal, Linlin You |
| 2024 | WWW | Exploring Representational Similarity Analysis to Protect Federated Learning from Data Poisoning. | Gengxiang Chen, Kai Li, Ahmed M. Abdelmoniem, Linlin You |
| 2023 | EuroSys | REFL: Resource-Efficient Federated Learning. | Ahmed M. Abdelmoniem, Atal Narayan Sahu, Marco Canini, Suhaib A. Fahmy |
| 2023 | IPCCC | Achieving Zero-copy Serialization for Datacenter RPC. | Tianfan Zhang, Huaping Zhou, Chengyuan Huang, Chen Tian, Wei Zhang, Xiaoliang Wang, Yi Wang, Ahmed M. Abdelmoniem, Matthew Tan, Wanchun Dou, Guihai Chen |
| 2022 | EuroSys | Empirical analysis of federated learning in heterogeneous environments. | Ahmed M. Abdelmoniem, Chen-Yu Ho, Pantelis Papageorgiou, Marco Canini |
| 2021 | EuroSys | Towards Mitigating Device Heterogeneity in Federated Learning via Adaptive Model Quantization. | Ahmed M. Abdelmoniem, Marco Canini |
| 2021 | ICDCS | GRACE: A Compressed Communication Framework for Distributed Machine Learning. | Hang Xu, Chen-Yu Ho, Ahmed M. Abdelmoniem, Aritra Dutta, El Houcine Bergou, Konstantinos Karatsenidis, Marco Canini, Panos Kalnis |
| 2021 | INFOCOM | DC2: Delay-aware Compression Control for Distributed Machine Learning. | Ahmed M. Abdelmoniem, Marco Canini |
| 2020 | AAAI | On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning. | Aritra Dutta, El Houcine Bergou, Ahmed M. Abdelmoniem, Chen-Yu Ho, Atal Narayan Sahu, Marco Canini, Panos Kalnis |
| 2020 | CoNEXT | Huffman Coding Based Encoding Techniques for Fast Distributed Deep Learning. | Rishikesh R. Gajjala, Shashwat Banchhor, Ahmed M. Abdelmoniem, Aritra Dutta, Marco Canini, Panos Kalnis |