I was born and raised in Taipei, Taiwan.
I worked for Dr. Stella Yu and Prof. Meng C. Lin at ICSI (Berkeley), where I studied the unsupervised feature learning on meibography phenotype and self-driving. I received my Masters degree in Engineering Science from National Taiwan University, where I worked in Machine Learning and Vision. Previous to that, as an undergraduate I majored in Electrical Engineering.
The interaction between machine vision and human vision has grabbed my attention since I was applying the AI to meibomian gland images in one of my basic research. I found out the machine and human have completely different perceptions of vision by looking into meibography images. This brought me to explore how machine vision can simulate human vision and further to design a multi-functional vision system learned by machine to assist humans on different tasks. So I wanted to continue my research by moving into Berkeley Vision Science which offers a more multidisciplinary environment for me to investigate those unsolved problems.
I'm fascinated with unsupervised representation learning, especially on vision tasks and related applications. Specifically, my research is mainly focused on using unsupervised AI techniques to diagnose eye diseases (e.g., Meibomian gland dysfunction).
My final goal is to build up a world model, which includes representations learned by machine and covers not only human vision but a person's self-consciousness and body perceptions.
I enjoy watching movies and TV shows (Netflix), going to gym (Work out), and listening to Kpop songs (Koreaboo...). Sometimes, I like to plan road trips and hang out with friends for a special restaurant or spot.