publications

2026

1. IEEE ICCE

   

   ChronoSC: Task-Oriented Semantic Communication via Temporal-to-Color Encoding

   P. H. Nguyen , T. T. Nguyen, Q. N. Duong, and 1 more author

   In IEEE International Conference on Consumer Electronics (ICCE), May 2026

   Accepted

   Abs arXiv Bib HTML

   Task-oriented semantic communication (SC) is a promising paradigm to address bandwidth constraints and latency bottlenecks in video-based tasks such as Video Question Answering (VideoQA). We propose ChronoSC, a lightweight framework utilizing Chrono-Color Stacking to collapse video temporal dynamics into a single static image for efficient DeepJSCC transmission and direct consumption by pre-trained vision-language models.

   @inproceedings{nguyen2026chronosc,
     title = {ChronoSC: Task-Oriented Semantic Communication via Temporal-to-Color Encoding},
     author = {Nguyen, P. H. and Nguyen, T. T. and Duong, Q. N. and Nguyen, Van-Dinh},
     booktitle = {IEEE International Conference on Consumer Electronics (ICCE)},
     year = {2026},
     month = may,
     note = {Accepted}
   }

2. IEEE TCSV

   

   FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition

   H.-P. Nguyen , B. H. Ngo, M. P. Tran, and 1 more author

   IEEE Transactions on Circuits and Systems for Video Technology, Jul 2026

   Major Revision

   Abs arXiv Bib HTML Code Website

   Fine-grained aquatic species recognition is inherently challenging due to extreme phenotypic similarities among related species and severe class imbalance in real-world distributions. In this paper, we propose FISHER, a gradient-decoupled hierarchical multi-task learning framework coordinating segmentation, morphological trait identification, and fine-grained classification. By decoupling conflicting task gradients and aligning trait prototypes, FISHER achieves state-of-the-art accuracy and significant gains on ultra-rare species.

   @article{nguyen2026fisher,
     title = {FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition},
     author = {Nguyen, H.-P. and Ngo, B. H. and Tran, M. P. and Nguyen, Van-Dinh},
     journal = {IEEE Transactions on Circuits and Systems for Video Technology},
     year = {2026},
     month = jul,
     note = {Major Revision},
   }

3. Arxiv

   

   C-MambaPose: A Physics-Informed Complex Mamba Framework for Cross-Environment WiFi Human Pose Estimation

   Phuc H. Nguyen

   Jul 2026

   Arxiv preprint

   Abs arXiv Bib HTML

   Cross-environment WiFi-based human pose estimation (HPE) suffers from severe domain shift caused by environmental multipath variations. We introduce C-MambaPose, a physics-informed complex Mamba framework that processes complex-valued Channel State Information (CSI) by decoupling phase and amplitude dynamics with complex state space models to achieve robust cross-environment 3D pose estimation.

   @misc{nguyen2026cmambapose,
     title = {C-MambaPose: A Physics-Informed Complex Mamba Framework for Cross-Environment WiFi Human Pose Estimation},
     author = {Nguyen, Phuc H.},
     year = {2026},
     note = {Arxiv preprint}
   }

2025

1. IEEE Commun. Lett.

   

   Energy-Aware Resource Allocation for Energy Harvesting Powered Wireless Sensor Nodes

   Minh Ngoc Ngo , Thanh Trung Nguyen , Hong-Phuc Nguyen, and 1 more author

   IEEE Communications Letters, Mar 2025

   Abs DOI arXiv Bib HTML

   Low harvested energy poses a significant challenge to sustaining continuous communication in energy harvesting (EH)-powered wireless sensor networks. In this paper, we introduce a novel energy-aware resource allocation problem aimed at enabling the asynchronous accumulate-then-transmit protocol. We jointly optimize power allocation and time fraction dedicated to EH to maximize average long-term system throughput, accounting for both data and energy queue lengths.

   @article{ngo2025energyaware,
     title = {Energy-Aware Resource Allocation for Energy Harvesting Powered Wireless Sensor Nodes},
     author = {Ngo, Minh Ngoc and Nguyen, Thanh Trung and Nguyen, Hong-Phuc and Nguyen, Van-Dinh},
     journal = {IEEE Communications Letters},
     volume = {29},
     number = {3},
     pages = {542--546},
     year = {2025},
     month = mar,
     doi = {10.1109/LCOMM.2024.3369687},
   }