I have joined IBM Almaden Research Center since September 2017.
I received my Ph.D. degree in 2017 from National University of Singapore, where I was affiliated with the Database Group (advisor: Kian-Lee Tan). Previously, I was a visiting research scholar at the Database Group, Carnegie Mellon University (host advisor: Andrew Pavlo), a research intern at the System Group, Microsoft Research Asia, and a research intern at the Cloud Infrastructure Group, EMC Labs China. I earned my bachelor's degree from South China University of Technology in 2012.
My research focuses on designing and implementing high performance database management systems (DBMSs) with modern hardware support. The ultimate goal is to enable DBMSs to achieve scalable on-line transaction processing in the main-memory and multi-core settings. This requires a complete redesign of several major DBMS components, including concurrency control, storage management, and fault tolerance.
I also have particular interests in designing and implementing distributed systems.
Peloton: The Self-Driving Database Management System. [project]
Cavalia: A Transactional Main-Memory Database on Multicores. [project]
Fast Failure Recovery for Main-Memory DBMSs on Multicores. [paper]
Yingjun Wu, Wentian Guo, Chee-Yong Chan, and Kian-Lee Tan.
An Empirical Evaluation of In-Memory Multi-Version Concurrency Control. [paper]
Yingjun Wu, Joy Arulraj, Jiexi Lin, Ran Xian, and Andrew Pavlo.
Self-Driving Database Management Systems. [paper]
Andrew Pavlo, Gustavo Angulo, Joy Arulraj, Haibin Lin, Jiexi Lin, Lin Ma, Prashanth Menon, Todd Mowry, Matthew Perron, Ian Quah, Siddharth Santurkar, Anthony Tomasic, Skye Toor, Dana Van Aken, Ziqi Wang, Yingjun Wu, Ran Xian, and Tieying Zhang.
Transaction Healing: Scaling Optimistic Concurrency Control on Multicores. [paper]
Yingjun Wu, Chee-Yong Chan, and Kian-Lee Tan.
ChronoStream: Elastic Stateful Stream Computation in the Cloud. [paper]
Yingjun Wu and Kian-Lee Tan.
SocialTransfer: Transferring Social Knowledge for Cold-Start Crowdsourcing. [paper]
Zhou Zhao, James Cheng, Furu Wei, Ming Zhou, Wilfred Ng, and Yingjun Wu.
Grand challenge: SPRINT Stream Processing Engine as a Solution. [paper]
Yingjun Wu, David Maier, and Kian-Lee Tan.
DEBS 2013. (Best Paper Award)
Understanding the Effects of Hypervisor I/O Scheduling for Virtual Machine Performance Interference. [paper]
Ziye Yang, Haifeng Fang, Yingjun Wu, Chunqi Li, Bin Zhao, and H. Howie Huang.
Optimization Of OLTP Database Systems Through Program Analysis.
Carnegie Mellon University, Pittsburgh, PA, USA, May 2017. [link]
Brown University, Providence, RI, USA, May 2017.
Building Faster Main-Memory Database Management Systems on Multicores.
National University of Singapore, Singapore, October 2016. [link]
This is the Best Paper Ever on In-Memory Multi-Version Concurrency Control.
Carnegie Mellon University, Pittsburgh, PA, USA, September 2016. [link]
Scalable In-Memory Transaction Processing with HTM.
Carnegie Mellon University, Pittsburgh, PA, USA, June 2016.
Transaction Healing: Scaling Optimistic Concurrency Control on Multicores.
Carnegie Mellon University, Pittsburgh, PA, USA, March 2016. [link]
ChronoStream: Elastic Stateful Stream Computation in the Cloud.
National University of Singapore, Singapore, May 2015.
Program Committee: SIGMOD 2018 (Demo).
Journal Reviewer: TKDE, TPDS.
CS3103: Computer Networks and Protocols.
National University of Singapore, 2014-2015.
Last update: September 20th, 2017