About.

Hi, I’m Winnie, an undergraduate studying Chemical Engineering and Computer Science at National Tsing Hua University (NTHU), Taiwan.

My research interests revolve around representation learning that respects the symmetries of nature. I am especially interested in applying these ideas to molecular and quantum many-body problems where established methods struggle.

At Caltech’s Anima AI+Science Lab, I’m part of the AI for chemistry group, advised by Prof. Anima Anandkumar. My latest work focuses on SU(2)-equivariant graph neural networks for molecular magnetism arising from spin-orbit-coupling. Currently, at NTHU’s Lab for Material and Molecular Design, I’m developing a transferable machine learning method for vibrational circular dichroism spectra with Prof. Kun-Han Lin. My earlier work there includes building an automated force-field parameterization toolkit and studying high-entropy alloys for the hydrogen evolution reaction using density functional theory.

I’m also an LLM research intern (part-time) at the National Center for High-Performance Computing (NCHC). Previously, as captain of the NTHU Student Cluster Competition Team, I led our team (The Aincrad Progressors) at national, Asia-Pacific, and international competitions. More details are in my CV.