Nguyen Hong Phuc

Ha Noi, Vietnam

23phuc.nh@vinuni.edu.vn

+84 326 060 805

🎓 Ph.D. Research — Fall 2027: I am interested in fully funded Ph.D. programs in Wireless Sensing, Wireless Communications, AI/ML, and Signal Processing. If you are interested in discussing potential research alignment, please feel free to reach out!

I am an Electrical and Computer Engineering student at VinUniversity, specializing in wireless sensing, signal processing, and AI/ML for physical-world perception. My recent work is increasingly focused on wireless sensing and robust perception, building on my earlier research in semantic communication and computer vision.

I am currently a Research Intern at HKU AIoT Lab, The University of Hong Kong (Jul. 2026 – Present), supervised by Prof. Chenshu Wu, working on thermal and RF sensing research. I also conduct research as an Undergraduate Research Assistant at the Intelligence, Computing and Communication Lab (ICCL) at VinUniversity & Trinity College Dublin, under the supervision of Assist. Prof. Nguyen Van Dinh, where I lead a $3,500 Student Research Grant on smart multi-sensory aquaculture systems.

Research interests:

Primary:
- Wireless Sensing & Signal Processing (WiFi CSI, RF & thermal perception, pose estimation)
- AI/ML for Physical-World Perception (physics-informed models, state space models / Mamba)
- Wireless Communications & Semantic Communication (task-oriented semantic coding, DeepJSCC)
Secondary / Supporting:
- Human sensing & activity recognition · Domain generalization · Edge AI & embedded IoT systems

Education:

BSc in Electrical and Computer Engineering, VinUniversity (Oct. 2023 – Present)
GPA: 3.80/4.00 · Rank 1 in ECE Cohort 4 · 2× President’s List (AY 23–25) · Dean’s List (5 Semesters) · 100% Talent Scholarship (2023–2027)
Australia-Vietnam Strategic Technologies Scholarship · Best Poster Award OIC 2025
Bac Ninh High School for the Gifted, Physics Major (2020 – 2023)
GPA: 9.6/10 · 2nd Prize National Physics Olympiad (2023) · Gold Medal High School Olympiad (2021–2022) · 5th Place Thomas Jefferson Physics Olympiad (2023)

Professional Activities:

Technical Program Committee (TPC): 2026 RIVF International Conference on Computing and Communication Technologies
Invited Reviewer: IEEE Transactions on Cognitive Communications and Networking
Invited Reviewer: IEEE International Conference on Advanced Technologies for Communications (ATC) 2026

news

Aug 22, 2026	🎓 Ph.D. Research — Fall 2027: Looking for fully funded Ph.D. positions in Wireless Sensing, Wireless Communications, AI/ML, and Signal Processing. Feel free to connect via email!
Jul 02, 2026	Starting as a Research Intern at HKU AIoT Lab, The University of Hong Kong — selected as 1 of 40 students for a fully funded internship, supervised by Prof. Chenshu Wu.
Jun 01, 2026	Invited as Reviewer for IEEE Transactions on Cognitive Communications and Networking and IEEE ATC 2026.
May 24, 2026	Paper ChronoSC: Task-Oriented Semantic Communication via Temporal-to-Color Encoding accepted at IEEE ICCE 2026!
Mar 01, 2026	Awarded a $3,500 Student Research Grant to lead research on smart aquaculture IoT and multimodal AI systems at VinUniversity.

selected publications

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

Phuc H. Nguyen

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

P. H. Nguyen , T. T. Nguyen, Q. N. Duong, and Van-Dinh Nguyen

In 2026 IEEE 11th International Conference on Communications and 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 = {2026 IEEE 11th International Conference on Communications and Electronics (ICCE)}, year = {2026}, month = may, note = {Accepted} }
Major Revision
FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition

H.-P. Nguyen , B. H. Ngo, M. P. Tran, and Van-Dinh Nguyen

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.
@misc{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}, year = {2026}, month = jul, note = {Major Revision}, }
IEEE Commun. Lett.
Energy-Aware Resource Allocation for Energy Harvesting Powered Wireless Sensor Nodes

N. M. Ngo , T. T. Nguyen , H.-P. Nguyen, and Van-Dinh Nguyen

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, N. M. and Nguyen, T. T. and Nguyen, H.-P. 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}, }