I am a PhD student at HKUST (Guangzhou), working with Prof. ZHANG Tong-Yi. My research focuses on artificial intelligence for materials science, with particular emphasis on algorithm development for crystallography and spectroscopy. During my PhD, I also served as a visiting student at City University of Hong Kong, working with Prof. REN Yang.

Before joining HKUST (Guangzhou), I earned an MPhil in Mechanics at Shanghai University, working with Prof. ZHANG Tong-Yi. During this period, I also interned at Zhejiang Laboratory, where I worked on transfer learning for materials science. I received my BEng in Chemical Machinery from Beijing University of Chemical Technology, where my work focused on finite element and chemistry.

In recent years, I developed a series of machine-learning algorithms for crystal structure determination (XQueryer), crystal property prediction (PRDNet), and novel crystal discovery (SimXRD). My first-author papers have appeared in materials science journals (e.g., National Science Review and Science Bulletin) and AI conferences such as ICLR.

One of my long-term projects, Bgolearn, received support from the Shanghai Artificial Intelligence Open Source Award Project Support Plan, where I serve as the principal developer. The project was awarded RMB 500,000 to support the development of the open-source Bgolearn platform. Outside of research, I enjoy jogging and watching movies.

I am a strong proponent of open science, advocating for transparency, reproducibility, and community collaboration in computational research.

Due to the large number of messages I receive, I kindly ask that you first take a moment to clarify your questions and review the repository README before reaching out.

As many common questions (e.g., debugging, file paths, resource allocation, or general usage) are already addressed in the documentation, I may be unable to reply to individual emails on these topics. For quicker and more effective support, opening a GitHub Issue is highly recommended.

To help me respond appropriately, please include your name, affiliation, and the purpose of your message. Messages without this information may not receive a reply. For students interested in collaboration, please obtain prior approval from your supervisor and ensure that your supervisor is CC’ed on any correspondence. Thank you very much for your understanding and interest.

📌 Quick Links

🔬 Academic Introduction | 🏠 Personal Website | 📖 Google Scholar Profile

Feel free to contact Mr. CAO Bin at: 📧 Email: bcao686@connect.hkust-gz.edu.cn 📧 Email: bincao4-c@my.cityu.edu.hk Infinite possibilities start with your next line of code.