• Deploy machine learning/computer vision algorithms for surveillance systems such as: protection equipment detection, human fall down detection, fire and smoke detection, etc.• Develop computer vision - based web app for public camera monitoring systems: traffic tracking, accident detection.• Develop active learning/online learning process to build fast, accurate, adaptive Deep Learning models for ML/CV systems.

• Research and develop ranking algorithms on public blockchain transaction networks.• Publications:1. Huu-Dung Do and Thuat Do, “PageRank on Blockchain Transactions and a Measure for Social Credit”, IEEE International Conference on Big Data, Cloud Computing, and Data Science Engineering, August 2022.2. Huu-Dung Do and Thuat Do, “PageRank and HodgeRank on Ethereum Transactions: a Measure for Social Credit”, International Journal of Software Innovation (IJSI), under review.

• Deploy machine learning/computer vision techniques to classify food quality during preservation, considering full pipeline from raw data until the decision layer.• Research and deploy state of the art techniques in the field of computer vision, ML and DL.• Publications:1. Huu-Dung Do and Wan-Young Chung, “A Deep Learning Approach for Food Quality Classification Based on RF Energy Harvesting and Mask-RCNN”, Conference of Korea Institute of Convergence Signal Processing, August 2020.2. Huu-Dung Do, Dong-Eon Kim, and Wan-Young Chung, “Accurate Food Quality Estimation Using Long Short-Term Memory Neural Networks and RF Energy Scavenging”, Conference of Korea Institute of Convergence Signal Processing, December 2020.3. Huu-Dung Do, Lam Binh Minh, Dong-Eon Kim, and Wan-Young Chung, “Self-Powered Food Assessment System Using LSTM Network and 915MHz RF Energy Harvesting”, IEEE Access, vol.9, pp. 97444-97456, 2021.

• Virtual Try-On Clothes (2020): understanding and implementing code of the state-of-the-art deep learning method (ACGPN/Cloth-VTON) for virtual clothing try-on problem, transferring a clothing image onto a target person image. Python/PyTorch.• Low-cost Face Recognition Thermometer Camera (2020): build a low-cost system that combined face recognition with infrared thermography to realize close range, contactless face recognition, and temperature detection. AMG8833 (Thermal sensor), Raspberry Pi (processing unit), Python/SSD-Face/Open-Face (Face Recognition/ UI).• Handwritten Text Recognition on Jetson nano dev kit (2019): build a detector for printed and handwritten text using Jetson nano kit, which is able to extend for a reading eye device for visually impaired people. Python/TensorFlow.• Electronic Price Tag System for Supermarket (2017): replaces paper price tag used in many supermarkets, contains price tag display nodes attached to product shelves and the web server sends price data to display on each node. C++ (embedded firmware), C#/HTML (Web UI).

I got a position in Viettel research center and worked with the quality assurance team to develop an automated testing software for eNodeB remote radio units in the LTE system.

My team researched and designed new embedded electronic products for real-life applications. Specifically, I developed and optimized firmware for the following systems:- Automatic Blood Shaking machine.- Thoracic suction machine.- Automated doorbell system.- Automatic water pump machine.