My research interests lie at the intersection of database systems and machine learning applications. Specifically, I researched designing machine learning models for database problems, e.g., cardinality estimation (SIGMOD'21) and database generation (SIGMOD'22). My recent work concerns building large-scale systems for provenance in text and social media.
03 2022 Paper on machine learning for database generation from query workloads accepted to SIGMOD 2022.
12 2021Shoushou just turned one year old!
08 2021 Starting my Ph.D. journey at Penn.
01 2021 UAE paper accepted to SIGMOD 2021.
SAM: Database Generation from Query Workloads with Supervised Autoregressive Models
Jingyi Yang*, Peizhi Wu*, Gao Cong, Tieying Zhang, Xiao He The 2022 ACM International Conference on Management of Data (SIGMOD) 2022 (To appear)
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation Peizhi Wu, Gao Cong The 2021 ACM International Conference on Management of Data (SIGMOD) 2021
A Meta-Path-Based Recurrent Model for Next POI Prediction with Spatial and Temporal Contexts
Hengpeng Xu, Peizhi Wu, Jinmao Wei, Zhenglu Yang, Jun Wang The third Asia Pacific Web and Web-Age Information Management Joint Conference on Web and Big Data (APWeb-WAIM) 2019
Neural Framework for Joint Evolution Modeling of User Feedback and Social Links in Dynamic Social Networks Peizhi Wu, Yi Tu, Xiaojie Yuan, Adam Jatowt and Zhenglu Yang The 27th International Joint Conference on Artificial Intelligence (IJCAI) 2018
dbCAN-seq: a database of carbohydrate-active enzyme (CAZyme) sequence and annotation
Le Huang, Han Zhang, Peizhi Wu, Sarah Entwistle, Xueqiong Li, Tanner Yohe, Haidong Yi, Zhenglu Yang, Yanbin Yin Nucleic Acids Research (NAR) 2017