We propose a quantum rationale-aware graph contrastive learning framework for jet discrimination in high-energy physics, combining graph neural networks with quantum computing to improve classification performance.
@article{masud2026quantumcontrastive,author={Jahin, Md Abrar and Masud, Md Akmol and Mridha, M. F. and Dey, Nilanjan},title={Quantum Rationale-Aware Graph Contrastive Learning for Jet Discrimination},journal={Transactions on Machine Learning Research},year={2026},url={https://arxiv.org/abs/2411.01642},}
MosQNet-SA: Explainable Convolutional-Attention Network for Mosquito Classification with Application as a RESTful API for Dengue and Malaria Risk Mapping
Md Akmol Masud, Sanjida Akter, Nadia Sultana, and 4 more authors
MosQNet-SA is an explainable convolutional-attention network for classifying mosquito species (Anopheles, Aedes, Culex) with integrated RESTful API for real-time dengue and malaria risk mapping.
@article{masud2026mosquito,author={Masud, Md Akmol and Akter, Sanjida and Sultana, Nadia and Islam, Mohammad Shahidul and Abu Yousuf, Mohammed and Noori, Farzan M. and Uddin, Md Zia},title={MosQNet-SA: Explainable Convolutional-Attention Network for Mosquito Classification with Application as a RESTful API for Dengue and Malaria Risk Mapping},journal={PLOS ONE},year={2026},volume={21},number={4},pages={1--30},doi={10.1371/journal.pone.0344970},url={https://doi.org/10.1371/journal.pone.0344970},}
BSPC
DREAM: A Novel Explainable Neural Network for Detecting Sleep Apnea Using Single-Lead ECG Signals
Sanjida Akter, Md Akmol Masud, Mst. Sanzida Islam Promi, and 6 more authors
DREAM is an explainable neural network for detecting sleep apnea from single-lead ECG signals, featuring novel explainability mechanisms for clinical interpretability.
@article{akter2026dream,author={Akter, Sanjida and Masud, Md Akmol and Promi, Mst. Sanzida Islam and Sultana, Nadia and Ahmed, Maruf and Rahman, Md. Mahmudur and Yousuf, Mohammad Abu and Aloteibi, Saad and Moni, Mohammad Ali},title={DREAM: A Novel Explainable Neural Network for Detecting Sleep Apnea Using Single-Lead ECG Signals},journal={Biomedical Signal Processing and Control},volume={114},pages={109291},year={2026},doi={10.1016/j.bspc.2025.109291},url={https://www.sciencedirect.com/science/article/pii/S1746809425018026},}
ICECTE
FedDQN-TSR: Federated Deep Q-Learning for Resource-Aware Traffic Sign Recognition in Internet of Vehicles
Zannat Hossain Tamim, Md Akmol Masud, Md. Sazzadur Rahman, and 1 more author
In 5th International Conference on Electrical, Computer & Telecommunication Engineering (ICECTE), 2026
FedDQN-TSR applies federated deep Q-learning for resource-aware traffic sign recognition in Internet of Vehicles environments, balancing communication efficiency and model accuracy.
@inproceedings{masud2026feddqn,author={Tamim, Zannat Hossain and Masud, Md Akmol and Rahman, Md. Sazzadur and Islam, Mohammad Shahidul},title={FedDQN-TSR: Federated Deep Q-Learning for Resource-Aware Traffic Sign Recognition in Internet of Vehicles},booktitle={5th International Conference on Electrical, Computer \& Telecommunication Engineering (ICECTE)},year={2026},pages={1--6},publisher={IEEE},doi={10.1109/ICECTE69292.2026.11429337},url={https://doi.org/10.1109/ICECTE69292.2026.11429337},}
HeteRo-Select is a client selection framework for federated learning under extreme statistical and system heterogeneity, featuring variance-aware scheduling and heterogeneity-aware aggregation strategies.
@misc{masud2025heteroselect,author={Masud, Md Akmol and Jahin, Md Abrar and Hasan, Mahmud},title={Stabilizing Federated Learning under Extreme Heterogeneity with HeteRo-Select},year={2025},url={https://arxiv.org/abs/2508.06692},}
IEEE TAI
Lorentz-Equivariant Quantum Graph Neural Network for High-Energy Physics
Md Abrar Jahin, Md Akmol Masud, Md Wahiduzzaman Suva, and 2 more authors
IEEE Transactions on Artificial Intelligence, 2025
A Lorentz-equivariant quantum graph neural network for jet classification in high-energy physics, exploiting physical symmetries via quantum circuits for improved discrimination.
@article{jahin2025lorentz,author={Jahin, Md Abrar and Masud, Md Akmol and Suva, Md Wahiduzzaman and Mridha, M. F. and Dey, Nilanjan},title={Lorentz-Equivariant Quantum Graph Neural Network for High-Energy Physics},journal={IEEE Transactions on Artificial Intelligence},year={2025},pages={1--11},doi={10.1109/TAI.2025.3554461},url={https://doi.org/10.1109/TAI.2025.3554461},}
KACQ-DCNN combines classical and quantum computing in a dual-channel neural network with Kolmogorov-Arnold representations for interpretable, uncertainty-aware heart disease detection.
@article{jahin2025kacq,author={Jahin, Md Abrar and Masud, Md Akmol and Mridha, M. F. and Aung, Zeyar and Dey, Nilanjan},title={KACQ-DCNN: Uncertainty-Aware Interpretable Kolmogorov--Arnold Classical--Quantum Dual-Channel Neural Network for Heart Disease Detection},journal={Computers in Biology and Medicine},year={2025},volume={197},pages={110976},doi={10.1016/j.compbiomed.2025.110976},url={https://doi.org/10.1016/j.compbiomed.2025.110976},}
ECCE
Multi-Layered Password-Based Steganography: A Novel Approach for Tiered Information Hiding
Md Akmol Masud, Sanjida Akter, Nadia Sultana, and 2 more authors
In International Conference on Electrical, Computer and Communication Engineering (ECCE), 2025
A multi-layered password-based steganography system for tiered information hiding with hierarchical access control and improved security against steganalysis.
@inproceedings{masud2025ecce,author={Masud, Md Akmol and Akter, Sanjida and Sultana, Nadia and Yousuf, Mohammad Abu and Uddin, Md Zia},title={Multi-Layered Password-Based Steganography: A Novel Approach for Tiered Information Hiding},booktitle={International Conference on Electrical, Computer and Communication Engineering (ECCE)},year={2025},pages={1--6},publisher={IEEE},doi={10.1109/ECCE64574.2025.11013270},url={https://doi.org/10.1109/ECCE64574.2025.11013270},}
