Jinglin Peng Email and Phone Number

I'm working on interactive data analytics, which is a challenging problem when extracting insights from large scale data. More specifically, I focus on two lines of research:(1) Approximate Query Processing (AQP): The goal of AQP is to 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) Exploratory Data Analytics (EDA): The goal of my research is to simplify the EDA process. We've designed and implemented the first task-centric 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 ~1000 stars and has been downloaded ~200K times.