acknowledgements

The work presented on this site is my own, but much of it depended on guidance, collaboration and public resources. This page records those debts.

Teachers

Thanks to the teachers who supervised my research training. I started participating in projects in my first year, beginning with data splits and experiment records and gradually taking on algorithm implementation. During a period when most experiments failed, my supervisors allowed ample room for trial and error while correcting my methods, which shaped how I design and document experiments.

Thanks also to the teachers in my original major, who gave concrete advice during my cross-disciplinary study and transfer preparation.

Teammates and collaborators

Competitions and projects were mostly team efforts. The medical imaging projects involved members with biomedical engineering and computer science backgrounds, while I focused on algorithms and software implementation. I am grateful for their work on data organisation, clinical context and written material.

Family

Thanks to my family for their support and understanding of my decision to transfer majors and of the time I have spent on competitions and research.

Open source

Most of this work stands on open-source foundations: PyTorch and public medical imaging datasets, VitePress and a wide range of tooling; much of my troubleshooting drew on public documentation and community discussion. In return, I open-source my own code and write up engineering experience as notes.

Note

This site contains only my own work and publicly available information. It does not include student identifiers, phone numbers or national ID numbers; the only contact channels are the public email, WeChat and GitHub links. No other person's name appears on the site, and no unpublished third-party information is used.