A list of my peer-reviewed journal articles, conference papers, and preprints focusing on quantum/machine learning, federated learning, post/quantum security, wireless communications, Applied/AI, distributed network architectures etc.
View Google Scholar ProfileD. Gurung, et al. — Future Generation Computer Systems
Pioneering work on a continuous QFL framework that uses chained models for enhanced efficiency and resource optimization. (Q1, Core A Journal)
D. Gurung, et al. — IEEE Transactions on Network and Service Management
Comprehensive study and implementation of QFL architectures optimized for low-latency, high-security Metaverse requirements.
D. Gurung, et al. — IEEE Transactions on Artificial Intelligence
Designing a novel weighted personalization strategy for QFL to improve model accuracy and fairness across heterogeneous client data distributions. (Q1 Journal)
D. Gurung, et al. — 40th International Conference on Information Networking (ICOIN)
A conceptual design and analysis of a quantum barrage relay network utilizing teleportation for high-speed, secure communication. (Core B Conference)
D. Gurung, et al. — Arxiv (Submitted)
A submission detailing a privacy-focused QFL approach optimized by the server for vehicular networks (V2X). (Submitted to A* Journal)
D. Gurung, et al. — Arxiv (Submitted)
Proposing a multi-layered privacy design utilizing various cryptographic protocols to enhance trust and security in QFL scaling. (Submitted to A* Journal)
D. Gurung, et al. — Arxiv (Submitted)
Introduction of a multilayer security framework (QuantumShield) to fortify QFL systems against various cyber and quantum threats. (Submitted to A* Journal)
D. Gurung, et al. — Arxiv (Submitted)
Designing a secure QFL model optimized for the unique constraints and latency challenges of Low Earth Orbit (LEO) satellite networks. (Submitted to Core A* Journal)
D. Gurung, et al. — Under Review (Internal)
A new hierarchical and clustered approach to personalized QFL, improving efficiency and relevance for large, diverse client pools. (Under Review)
D. Gurung, et al. — Arxiv
Exploring model distillation techniques to efficiently integrate Large Language Models (LLMs) within a QFL architecture. (Under Review)
D. Gurung, et al. — Arxiv
A detailed survey and critical analysis of the current state, open challenges, and future directions of Quantum Federated Learning. (Under Review)
D. Gurung, et al. — Arxiv
A quantum-enhanced federated learning system designed specifically for orbital mechanics and satellite data processing. (Under Revision)
D. Gurung, et al. — Computer Networks
Evaluation of integrating Post-Quantum Cryptography (PQC) with Blockchain-based Federated Learning to ensure long-term security. (Q1, Core A Journal)
D. Gurung, et al. — Proceedings of the 8th Asia-Pacific Workshop on Networking (APNet '24)
Foundational design and analysis of personalized model training within a Quantum Federated Learning framework.
D. Gurung, et al. — Arxiv
Developing an adaptive, model-driven QFL framework to significantly enhance communication efficiency, crucial for network constraints. (Under Major Revision, Core A*)
D. Gurung, et al. — 11th International Conference on Learning Representations (ICLR) Tiny Papers
Proof-of-concept demonstrating a robust and secure communication model tailored specifically for quantum-enabled federated environments. (ICLR Core A* Tiny Paper)