Responsibilities include:

• Lead a team of 5 AI engineers to develop a system to orchestrate APIs from agents to complex AI workflows.
• Research on vision-language model fine-tuning for understanding diagrams and flow charts, as well as social media pictures.
• Projects:
  • AI-Powered HR Solution (W-Hiring): Architected an AI-driven virtual HR employee system, enabling SMEs to streamline recruitment processes with minimal human intervention. Implemented advanced NLP models for resume parsing and candidate matching.
  • Intelligent Marketing Platform (G-Mate): Spearheaded the development of an AI-powered growth engine utilizing. Designed and implemented multi-modal AI models for user behavior analysis, content generation, and omni-channel distribution strategies.
  • AI-Driven Chatbot (Watt): Developed a conversational AI system for customer service and sales, leveraging transformer-based models for natural language understanding and generation. Implemented a multi-agent framework for orchestrating complex workflows and APIs.

Responsibilities include:

• Tech leader of a team of 7 AI and data engineers on the development and deployment of robot navigation and IoT analysis.
• Lead development of “Multi-embedding query for person MOT-ReID System”, which uses the innovative idea of pose-guided feature alignment to improve accuracy.
• Development of human action recognition and intrusion detection, with the combination of spatio-temporal and skeleton-based models. The algorithm has been deployed in applications like construction site surveillance and facility management.
• Construct an object detection/segmentation pipeline with quantization-aware mixed precision training on top of DETR and Mask2former. The pipeline also supports semi-automatic labelling and curriculum learning.
• Development of model quantization and acceleration on edge devices of all video analysis related algorithms in both C++ and Python. The target edge computing chips include Rocketchip RK3588 NPU and Sophgo TPU.
• Development of long-term time-series forecasting and classification for stock return forecasting, as well as time-series data from IoT sensors for anomaly detection, remaining useful life prediction.