I am a Ph.D candidate at University of Utah working with Prof. Feifei Li in the Data Group at University of Utah. I received my bachelor's degree from ACM Honored Class of Shanghai Jiao Tong University in 2015, and my research director at SJTU was Prof. Bin Yao. My research interests lie in designing distributed database management systems to handle big (spatial-temporal) data. Besides, I am also interested in main-memory database techniques and data privacy. A more detailed curriculum vitae is here.
I joined Penn State University as an assistant professor from Fall 2020. This homepage will have no further updates. Please refer to my new homepage.
FishStore is a new ingestion and storage layer for flexible- and fixed-schema datasets. It allows you to dynamically register complex predicates over the data, to define interesting subsets of the data. Such predicates are called PSFs (for predicated subset functions). FishStore performs partial parsing of the ingested data (based on active PSFs) in a fast, parallel, and micro-batched manner, and hash indexes records for subsequent fast PSF-based retrieval. To accomplish its goals, FishStore leverages and extends the FASTER hash key-value store, and uses an unmodified parser interface for fast parsing (we use simdjson in many of our examples).
Simba is a distributed in-memory spatial analytics engine based on Apache Spark. It extends the Spark SQL engine across the system stack to support rich spatial queries and analytics through both SQL and DataFrame query interfaces. Besides, Simba introduces native indexing support over RDDs in order to develop efficient spatial operators. It also extends Spark SQL's query optimizer with spatial-aware and cost-based optimizations to make the best use of existing indexes and statistics.
SEAL-ORAM is a unified testbed for evaluating the performance of different Oblivious RAM schemes including basic square root ORAM, hierachical ORAM, IBS-OS, TP-ORAM, BinaryTree-ORAM, etc. We also implemented recursive construction in this testbed as well. We did a comprehensive emperical evaluation on all these ORAM schemes and published the results in our VLDB 2017 paper.