Hi! I'm Long V. Nguyen (Nguyễn Viết Long in Vietnamse), a first-year PhD student majoring in Computer Engineering at ECE Department, Memorial University, Canada. During my research, I’m very fortunate to be advised by Prof. Trung Duong, a Canada Excellence Research Chair (CERC), and Prof. Octavia, a Canada Research Chair Tier-1. Before that, I graduated from the Elitech Program at Hanoi University of Science and Technology, Vietnam.
My main research interests are Machine Learning and Quantum Computing in Intelligent Networks, especially Semantic Communications for Vehicular Networks. With the efforts in these fields, our key objective is to seamlessly integrate the digital, physical and biological worlds to develop a "wireless without limit” connectivity in the realm of next-generation communication technology, contributing to the developments of Intelligent Transportation Systems.
I'm curious about everything novel and constantly seeking new learning opportunities, so don't hesitate to reach out if you have any questions or just want to connect!
When I'm not working, I enjoy reading 📖, swimming 🏊♂️, and playing my favorite sports like soccer ⚽️ and badminton 🏸.
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Selected Publications (view all )
Digital Semantic Communication with Neural Image Compression
L. V. Nguyen, T. T. Nguyen, O. A. Dobre, T. Q. Duong
IEEE International Conference on Computer Communications (INFOCOM) 2025 Conference
In this work, we introduce a neural image compression-enabled semantic communication system to enhance the efficiency of digital image transmission, named NCSC. By employing an accurate and adaptable entropy model, NCSC obtains the efficiently compressed bitstreams, which are compatible with digital communication systems. Incorporating with the well-established digital components, our system trained on the MS-SSIM metric can achieve a significant bandwidth compression ratio of 0.002 at low SNR, reducing remarkably transmission overhead.
Digital Semantic Communication with Neural Image Compression
L. V. Nguyen, T. T. Nguyen, O. A. Dobre, T. Q. Duong
IEEE International Conference on Computer Communications (INFOCOM) 2025 Conference
In this work, we introduce a neural image compression-enabled semantic communication system to enhance the efficiency of digital image transmission, named NCSC. By employing an accurate and adaptable entropy model, NCSC obtains the efficiently compressed bitstreams, which are compatible with digital communication systems. Incorporating with the well-established digital components, our system trained on the MS-SSIM metric can achieve a significant bandwidth compression ratio of 0.002 at low SNR, reducing remarkably transmission overhead.
Leveraging Stable Diffusion with Context-Aware Prompts for Semantic Communication
L. V. Nguyen, T. T. Nguyen, O. A. Dobre, T. Q. Duong
IEEE 21st International Conference on Mobile Ad-Hoc and Smart Systems (MASS) 2024 Conference
In this study, we present a novel Stable Diffusion-based semantic communication (SDSC) framework that demonstrates high performance, characterized by an elevated bandwidth compression ratio (BCR) and robust noise tolerance achieved by diffusion mechanism integrating supplementary prompts. This scheme significantly enhances the system's ability to preserve data integrity and meaning in noisy environments. By introducing additional context-aware prompts during transmission, we improve the accuracy of received information and mitigate the adverse effects of interference and noise.
Leveraging Stable Diffusion with Context-Aware Prompts for Semantic Communication
L. V. Nguyen, T. T. Nguyen, O. A. Dobre, T. Q. Duong
IEEE 21st International Conference on Mobile Ad-Hoc and Smart Systems (MASS) 2024 Conference
In this study, we present a novel Stable Diffusion-based semantic communication (SDSC) framework that demonstrates high performance, characterized by an elevated bandwidth compression ratio (BCR) and robust noise tolerance achieved by diffusion mechanism integrating supplementary prompts. This scheme significantly enhances the system's ability to preserve data integrity and meaning in noisy environments. By introducing additional context-aware prompts during transmission, we improve the accuracy of received information and mitigate the adverse effects of interference and noise.
All publications
Professional Activities
- Reviewer for IEEE Wireless Communications Letters
- Reviewer for International Conference on Communications (ICC)
- Reviewer for EAI Endorsed Transactions on Industrial Networks and Intelligent Systems