About Me

As an Assistant Manager on the AI Team within the Backend Department at Tridge, I am developing a news classifier leveraging large language models (LLMs). My work involves testing multiple versions of the model and implementing algorithms to enhance processing speed. I also contribute to improving the overall performance and efficiency of company systems.

Oversee end-to-end service management for the unmanned vending machine system, including team progress tracking and scheduling. Designed and maintained DevOps processes using Docker and Kubernetes to support system updates and modifications. Applied YOLOv8 for object detection, optimizing performance with TensorRT; used MobileNetV3 for classification tasks. Implemented object tracking algorithms based on ByteTrack and DeepSORT. Developed a decision-making algorithm leveraging a 'frame zone' approach to enhance system intelligence. Integrated ZeroMQ for lightweight messaging protocol support. Added optional MongoDB integration for storing external transaction data.

Image segmentation using U-Net architecture. Collaborate on writing algorithms as well as training a YOLOv5 and YOLOv7 model for book spine detection. Develop, train, and deploy a face detection model to an embedded board developed by KT&C. System automation and data pipeline handling using Apache Airflow, Docker, and AWS. Writing of Python scripts for crawling purposes. Database management including PostgreSQL and MongoDB.

Arduino-based IoT implementation for factory manufacturing using IR sensor. Data visualization using Python. Database and Ubuntu server management.

Trained a Face detection algorithm with multiple key points using torch. Develop a proposal flood monitoring project. Participate in Smart Farm and Smart Streetlights projects on the computer vision field.

Thesis: Edge-Cloud Computing on Multi-Domain Applications

Arduino-based IoT implementation. Cloud-based data processing for battery management system (BMS) and computer vision using AWS. Microcontroller coding with MATLAB Simulink and Arduino IDE. Data visualization using AWS Quicksight. Data streaming, storing and processing on AWS. Edge computing using Jetson NVIDIA devices, and Raspberry Pi. Application of machine learning for face detection, object detection and emotion recognition. Application of machine learning for face detection and image processing of thermal camera images. System development for real-time multimodal emotion recognition. Integration of wireless communication modules such as WiFi and LTE to a system. Patent writing, preparation and application.

Support Back-end Data Management. System testing and analysis. Oracle Database interface and familiar.

Thesis: Costiera: Online Hotel and Resort Reservation with Gmail Integration Log-in