I am a Smart Embedded Systems & IoT undergraduate student at Hanoi University of Science and Technology (HUST), conducting research at the EDABK Laboratory and building Efficient Edge AI systems.

• 🎓 B.S. in Smart Embedded Systems and IoT (Expected 2027) @ Hanoi University of Science and Technology (HUST)
• 🔬 Lab Member @ EDABK Laboratory, HUST
• 💼 Artificial Intelligence Intern @ Viettel Telecom & HANET Technology
• 🏆 2nd Place Winner & Top 100 Global Teams — HSIL Hackathon 2026 (Harvard Health Systems Innovation Lab)
• 🎖️ Outstanding Student — Global Consumer Intelligence Course 2025 (Matsuo-Iwasawa Lab, UTokyo)

• Efficient Edge AI: Developing, quantizing, and deploying real-time Computer Vision systems to balance extreme efficiency with high accuracy.

Computer Vision | NVIDIA DeepStream SDK| TensorRT | Jetson Nano

• Concept: High-throughput real-time product tracking at the edge using resource-constrained devices.
• Methodology: Built a parallelized DeepStream-based video pipeline processing 16 concurrent RTSP streams on a single Jetson Nano. Employed post-training FP16 quantization via TensorRT and knowledge distillation on YOLOv8n.
• Results: Sustained robust detection accuracy and real-time processing constraints at target distances up to 10 meters.
• [Code/Repository]

Real-time Object Tracking | YOLOv8 | Anchor Mapping | Industry 4.0

• Concept: Automating quality assurance in electronics manufacturing lines.
• Methodology: Deployed a custom-trained YOLOv8n detector tracking 11 component classes across a 2-tier packaging setup. Implemented a proprietary "Anchor-based Mapping" algorithm to synchronize state machines across 4 camera feeds.
• Results: Achieved low-latency error alerts for missing components, incorrect packaging order, or positioning errors.
• [Code/Repository]