Ratun Rahman

Ratun Rahman

he/him/his

Ph.D. Candidate | Quantum Computing · Machine Learning · Distributed AI

Publications

For the most current citation record, see my Google Scholar profile.

Selected Publications

  1. Rethinking Structured Generation: Can Graph-Based Reasoning Resolve Ambiguity?
    Ratun Rahman, Atit Pokharel.
    Advances in Neural Information Processing Systems (NeurIPS), 2026.

  2. Quantum Noise Mitigation with Adaptive Zero-Noise Extrapolation: A Contextual Multi-Armed Bandits Approach.
    Ratun Rahman, Dinh C. Nguyen.
    IEEE Journal on Selected Areas in Communications, 2026.
    Code

  3. Tackling Heterogeneity in Quantum Federated Learning: An Integrated Sporadic-Personalized Approach.
    Ratun Rahman, Shaba Shaon, Dinh C. Nguyen.
    IEEE Transactions on Computers, 2026.

  4. Quantum Convolutional Neural Networks: A Survey on Architectures, Applications, and Future Directions.
    Ratun Rahman, Dinh C. Nguyen.
    IEEE Transactions on Neural Networks and Learning Systems, 2026.

  5. Toward High-Precision Variational Quantum Sensing via Asynchronous Federated Learning.
    Ratun Rahman, Atit Pokharel, Dinh C. Nguyen.
    IEEE International Conference on Quantum Computing and Engineering (QCE), 2026.

  6. SimQFL: A Quantum Federated Learning Simulator with Real-Time Visualization.
    Ratun Rahman, Atit Pokharel, Dinh C. Nguyen.
    IEEE International Conference on Quantum Computing and Engineering (QCE), 2025.
    Code

Peer-Reviewed Journal Publications

  1. Tackling Heterogeneity in Quantum Federated Learning: An Integrated Sporadic-Personalized Approach.
    Ratun Rahman, Shaba Shaon, and Dinh C. Nguyen.
    IEEE Transactions on Computers, 2026.

  2. Quantum Convolutional Neural Networks: A Survey on Architectures, Applications, and Future Directions.
    Ratun Rahman and Dinh C. Nguyen.
    IEEE Transactions on Neural Networks and Learning Systems, 2026.

  3. Probabilistic Federated Learning on Uncertain and Heterogeneous Data with Model Personalization.
    Ratun Rahman and Dinh C. Nguyen.
    IEEE Transactions on Emerging Topics in Computational Intelligence, 2026.

  4. Escaping Barren Plateaus in Variational Quantum Algorithms Using Negative Learning Rate in Quantum Internet of Things.
    Ratun Rahman and Dinh C. Nguyen.
    IEEE Internet of Things Journal, 2025.

  5. Towards Heterogeneous Quantum Federated Learning: Challenges and Solutions.
    Ratun Rahman, Dinh C. Nguyen, Christo Kurisummoottil Thomas, and Walid Saad.
    IEEE Network, 2025.

  6. Quantum Federated Learning: A Comprehensive Survey.
    Md. Raihan Uddin, Shaba Shaon, Ratun Rahman, Dinh C. Nguyen, Octavia Dobre, and Dusit Niyato.
    IEEE Communications Surveys & Tutorials, 2025.

  7. When Quantum Federated Learning Meets Blockchain in 6G Networks.
    Dinh C. Nguyen, Md. Bokhtiar Al Zami, Ratun Rahman, Shaba Shaon, Tuy Tan Nguyen, and Fatemeh Afghah.
    IEEE Communications Standards Magazine, 2025.

  8. Towards Personalized Quantum Federated Learning for Anomaly Detection.
    Ratun Rahman, Sina Shaham, and Dinh C. Nguyen.
    IEEE Transactions on Network Science and Engineering, 2025.

  9. Semantic Communication-Aware Federated Fine-Tuning of Large Language Models.
    Samia Rahman and Ratun Rahman.
    IEEE Communications Letters, 2025.

  10. Electrical Load Forecasting over Multihop Smart Metering Networks with Federated Learning.
    Ratun Rahman, Pablo Moriano, Samee U. Khan, and Dinh C. Nguyen.
    IEEE Internet of Things Journal, 2025.

  11. Multimodal Federated Learning for Air Quality Estimation with Model Personalization over Aerial-Ground Networks.
    Ratun Rahman, Falguni Patadia, Jinhui Wang, and Dinh C. Nguyen.
    IEEE Geoscience and Remote Sensing Letters, 2025.

  12. Improved Modulation Recognition Using Personalized Federated Learning.
    Ratun Rahman and Dinh C. Nguyen.
    IEEE Transactions on Vehicular Technology, 2024.

  13. Best Practices for Facing the Security Challenges of Internet of Things Devices Focusing on Software Development Life Cycle.
    Ratun Rahman and Md. Rafid Islam.
    International Journal of Education and Management Engineering, 2023.

  14. A Survey of Software Metrics for Transitioning to an Updated Version of the Current Existing Framework or a New Framework.
    M. R. Islam, Ratun Rahman, A. Ahmed, and R. Jany.
    Journal of Electrical Electronics Engineering, 2022.

Peer-Reviewed Conference & Workshop Publications

  1. Rethinking Structured Generation: Can Graph-Based Reasoning Resolve Ambiguity?
    Ratun Rahman, Atit Pokharel.
    NeurIPS, 2026.

  2. Toward High-Precision Variational Quantum Sensing via Asynchronous Federated Learning.
    Ratun Rahman, Atit Pokharel, Dinh C. Nguyen.
    IEEE QCE, 2026.

  3. Differential Privacy for Distributed Quantum Sensing via Quantum Noise.
    Atit Pokharel, Ratun Rahman, Thomas Morris, Dinh C. Nguyen.
    IEEE QCE, 2026.

  4. SimQFL: A Quantum Federated Learning Simulator with Real-Time Visualization.
    Ratun Rahman, Atit Pokharel, Dinh C. Nguyen.
    IEEE QCE, 2025.

  5. Differentially Private Federated Quantum Learning via Quantum Noise.
    Atit Pokharel, Ratun Rahman, Shaba Shaon, Thomas Morris, Dinh C. Nguyen.
    IEEE QCE, 2025.

  6. Sporadic Federated Learning Approach in Quantum Environment to Tackle Quantum Noise.
    Ratun Rahman, Atit Pokharel, Dinh C. Nguyen.
    FedVision, CVPR Workshop, 2025.

  7. Quantum Federated Learning for Multimodal Data: A Modality-Agnostic Approach.
    Atit Pokharel, Ratun Rahman, Shaba Shaon, Thomas Morris, Dinh C. Nguyen.
    BEAM, CVPR Workshop, 2025.

  8. Multimodal Federated Learning with Model Personalization.
    Ratun Rahman, Dinh C. Nguyen.
    OPT: Optimization for Machine Learning, NeurIPS Workshop, 2024.

  9. False Data Injection Attack Detection in Edge-Based Smart Metering Networks with Federated Learning.
    Md. Raihan Uddin, Ratun Rahman, Dinh C. Nguyen.
    IEEE CCNC, 2024.

  10. Electrical Load Forecasting in Smart Grid: A Personalized Federated Learning Approach.
    Ratun Rahman, Dinh C. Nguyen.
    IEEE CCNC, 2024.

  11. Enabling Efficient Communication Using Federated Learning over Satellite Networks.
    Ratun Rahman, Dinh C. Nguyen.
    Von Braun Space Exploration Symposium, 2023.

  12. A Study of Permission-Based Malware Detection Using Machine Learning.
    Ratun Rahman, M. R. Islam, A. Ahmed, M. K. Hasan, H. Mahmud.
    International Conference on Security of Information and Networks (SIN), 2022.

Selected Current Manuscripts

  • Readout Noise Mitigation with Bayesian Methods for Quantum Neural Networks. — TNNLS, Revision 1 under review, 2026.
  • On Resource-Efficient Quantum Convolutional Neural Networks with Provable Convergence Guarantees. — TNNLS, under review, 2026.
  • Error-Mitigated Quantum Federated Learning over Heterogeneous Nodes under Dynamic Noise. — IEEE J-STSP, under review, 2026.
  • Scalable Malware Family Classification Using Quantum Kernel-Based Machine Learning. — IEEE TDSC, under revision, 2026.

Only selected ongoing manuscripts are shown here; the complete record is available in my CV.