Albert Au Yeung is currently the machine learning lead engineer at
Zwoop, a e-commerce start-up based in Hong Kong. He received his PhD
in Computer Science from the University of Southampton, UK, and MPhil
and BEng degrees from the Chinese University of Hong Kong.
He held research positions at NTT Communication Science Laboratories, Huawei's
Noah's Ark Lab, and the Hong Kong Applied Science and Technology
Research Institute. Further, he has been involved in various projects in
applied data mining and machine learning, including large scale
recommender systems, natural language processing, computer vision and
Web information extraction.
At Zwoop, he leads a team of machine learning engineers and data scientists to develop the core AI system
that is capable of extracting product details from e-commerce websites
and compare product semantically and visually across different merchants.
How To Create An AI System That Will Browse The Web Like A Human User
by Albert Au Yeung, Machine Learning Lead Engineer, Zwoop
Zwoop aims at assisting eCommerce customers to find the deals for desired products, and to automate the whole registration and checkout process.
This requires a system that can identify and compare products from any eCommerce website, understand the availability of the different variations, and know how to navigate through e-commerce websites. In this talk, Albert will discuss the process and challenges of applying a wide range of AI and machine learning technologies to create a system that can browse the Web like a human user. He will also discuss how AI can help to automate many other processes in daily life.