Responsibilities include: Machine Learning Model Validation

• Achieved speech recognition accuracy (English, Cantonese, Mandarin) through meticulous data validation with Large Language Models (LLMs).

Responsibilities include: Object Detection Model Building

• Utilized object detection models such as YOLO to identify LED screens, enhancing the decision-making process for clients in selecting suitable LED screens with 90% accuracy.
• Conducted end-to-end data analysis, from data exploration and cleaning to model building and outcome alignment with client requirements.

Responsibilities include: Backend Development and Data Pipeline Optimization

• Developed and maintained integrations with external eSports data providers to verify odds values.
• Engineered and managed the miss-game pipeline using AWS Lambda, S3, and DynamoDB.
• Designed and optimized the games’ data pipeline to ensure data integrity and usability for predictive analytics.
• Refactored code to remove unnecessary try-except blocks, improving overall code quality and performance.

Responsibilities include: Building a Multi-Agent System for Real-Time Conversations Between Humans and AIs

• Contributed to the development of a Multi-Agent System that facilitates real-time interaction between humans and AI from scratch, enhancing user experience and system responsiveness.
• Optimized the Recommender Systems with 10000 virtual user profile.

Responsibilities include: Machine Learning for Code and Documentation

• Applied LLMs to analyze and interpret metamodels, using a common set of metadata for benchmarking and testing ontology matching algorithms.
• Validated the precision, recall, and F1 score of the performance metrics for ontology matching algorithms.

Responsibilities include: Machine Learning for Code and Documentation

• Integrated Large Language Models (LLMs) to improve Software Engineering practices, particularly in code generation and documentation.
• Developed and deployed web-based tools using React.js, facilitating the use of LLMs by software engineers.

Responsibilities include: Software and Hardware Development

• Engineered a 3D-aware localization system that significantly improved spatial accuracy using UWB technology.
• Programmed and refined the collision detection algorithm, enhancing the precision of the positioning system.
• Developed a user-friendly GUI to control and monitor the system, improving user engagement and system manageability.

Responsibilities include: Using MAML, DRL, and other AI techniques in Human-Robot Collaboration

• Project 1: Meta-reinforcement Learning Based Control Approach for Assisting HRC in Personalized Production (2021/12-2022/08)
• Keywords: Model diagnostic meta-learning, Proximal policy optimization DRL, Robotics Perception
• • Awarded paper by HKIE
• • Designed self-learning robotic assisted systems (SLRAS) with self-adapt DRL algorithms to assist human operators
• • Enhanced the performance by about 75% on average
• Project 2: Mutual Cognitive Human-Robot Collaborative Manufacturing System (2022/01-2023/02)
• Keywords: Deep Reinforcement Learning, Augmented Reality, HRC
• • Awarded HKICT Student Innovation Grand Award and Gold Award and APICTA Award
• • Integrated virtual and realistic task planning and dynamic guidance of visual data to enhance the intelligence of robots and to facilitate information sharing with Augmented Reality
• • Conducted human-in-the-loop control approaches