My current project is WEBnm@ V.3, a webtool for comparing protein flexibility. In the latest version (V.3), we refactored the whole website from the front-end to the back-end, and the bioinformatic API, to provide the user a better user experience with regard to the website interactive design and the computing performance.
From Jun. to Oct. 2019, I organized a small programming course for 0-background beginners. This course was originally aiming at helping our group colleagues (female) with purely biological background to get familiar with the programming world, set up basic tools, and learn minimum Python programming, while later on, it became a small gathering place for PhDs in the department who wants to improve their programming skills, regardless of gender.
Having been in the gender imbalanced world of computer science (usually 1:10~20 from my experience) for a decade, I understand how hard it is to get started with programming, especially for women. As frequently receiving inquiries about learning programming, which shows the high demands of computing skills in the scientific world nowadays, I plan to start another round of programming course in late 2020, and this time scientific data processing with Python or R will be the main topic.
Feel free to leave me a message if you're interested in this idea.
My interests are mainly programming language theory, parallel computing and computation theory. I studied a data-parallel functional programming language in my master's thesis, which is titled Formalizing the Implementation of Streaming NESL.