Jiying Z
- Research Program Mentor
MS Master of Science
Expertise
Anything related to data science, machine learning and AI, social sciences, and the arts!
Project ideas
Community Analysis:
Is there some issue you've been aching to know more about in your community? For example, what student characteristics contribute to higher academic performance, and how can we help raise performance for the underserved? Is crime rate shifting in some way, and what might be the reasons? Is a local effort creating the impact that it wants? Together we can come up with an interesting topic and conduct a research project from data collection to applying most commonly used statistical techniques, culminating in an article for your school or local newspaper to bring awareness and insight into the issue.
Machine Learning:
The possibilities are endless here. Whether you're interested in creating a song recommendation system for your friends or taking on a Kaggle challenge (that's a well-known machine learning competition platform, by the way), I can help you navigate through all the essentials of building an end-to-end machine learning workflow. You will learn about common issues and nifty ways to tackle them as well!
History of statistics and mathematics:
Each concept in STEM subjects is rich with their very own history. Pick a STEM topic you are interested in (e.g. sampling techniques, or a certain machine learning method you've heard of), and do research into how it came about and what it has developed into now. Extra brownie points if you can identify ways to improve it! Write up your findings into a blog post and share it with the community.
Coding skills
R, Python, SQL,Reviews
"Polygence was a great experience for me. Jiying was really prepared in all of the sessions and spread the workload out evenly throughout the 10 weeks so that writing the final report wasn't too overwhelming. During each meeting, I learned about some new aspect of modeling or analyzing data that would advance the project. For homework, Jiying kept the options pretty open. I had the freedom to explore whichever part of the data I was most drawn to, and then we would discuss in the next session. Overall, I had a lot of fun and learned interesting concepts beyond the scope of a typical high school course."