I'm a Ph.D. student at Database System Lab in Simon Fraser University, supervised by Prof. Jiannan Wang. Before joining SFU, I got my B.Sc. degree from Harbin Institute of Technology. My research focuses on speeding up data analytics. Data analytics is a human-in-the-loop process and involves both human and machine. Therefore, I focus on two lines of research to speed it up:

• (1) Reduce Machine Time: In this line of research I consider sampling as the basic approach to reduce the data processed by machine and focus on Approximate Query Processing (AQP). An AQP system can approximately process analytical queries(e.g., SUM, COUNT, AVG, ...) over large scale data (TB/PB) interactively (e.g., within seconds) and accurately (e.g., with a small confidence interval). I've built an AQP system that combines samples and cubes to improve the estimation quality (by 10X), a sampler combination framework that selects and combines multiple samplers to answer the given query, and a new online aggregation system that is designed for partitioned data.


• (2) Reduce Human Time: In this line of research I focus on how to simplify each task that humans need to do. I've led the development of the first task-centric Exploratory Data Analytics (EDA) system in Python: DataPrep.EDA. It makes a good balance among three goals: easy to use, interactive speed and easy to customize. Since its first release, DataPrep has received ~1100 stars and has been downloaded ~250K times. Furthermore, We also build systems to simplify data preprocessing and machine learning debugging.