Yingjun Wu

Founder and CEO
RisingWave Labs
yingjunwu@risingwave-labs.com


About Me

I am the founder of RisingWave Labs, a startup innovating next-generation database systems. Before launching the startup, I was a software engineer at the Redshift team, Amazon Web Services, and a researcher at the Database group, IBM Almaden Research Center. I received my PhD degree from National University of Singapore, where I was affiliated with the Database Group (advisor: Kian-Lee Tan). I was also a visiting PhD student at the Database Group, Carnegie Mellon University (host advisor: Andrew Pavlo). I earned my bachelor's degree from South China University of Technology.

I am passionate about integrating research into real-world system products. During my time in AWS, I was responsible for boosting Amazon Redshift performance using advanced vectorization and compression techniques. Before that, I participated in the development of IBM Db2 Event Store's indexing structure and transaction processing mechanism. During my PhD, I developed two main-memory DBMS prototypes, namely Peloton and Cavalia. I was also an early contributor to Stratosphere, which is now widely known as Apache Flink.

We are hiring top talents globally. If you are enthusiastic in innovating next-generation database systems, let's connect and talk!

PhD Thesis

Title: Transaction Management In Multi-Core Main-Memory Database Systems. [thesis]
Thesis Committee: Bingsheng He, Yong Meng Teo, Alan Fekete.

Publications

(I do not update this website frequently. Please check out my Google Scholar profile for updates.)

WiSer: A Highly Available HTAP DBMS for IoT Applications. [paper]
Ronald Barber, Christian Garcia-Arellano, Ronen Grosman, Guy Lohman, C. Mohan, Rene Muller, Hamid Pirahesh, Vijayshankar Raman, Richard Sidle, Adam Storm, Yuanyuan Tian, Pinar Tozun, and Yingjun Wu.
IEEE BigData 2019.

HERMIT in Action: Succinct Secondary Indexing Mechanism via Correlation Exploration. [paper]
Yingjun Wu, Jia Yu, Yuanyuan Tian, Richard Sidle, and Ronald Barber.
VLDB 2019. (Demo Track)

Designing Succinct Secondary Indexing Mechanism by Exploiting Column Correlations. [paper]
Yingjun Wu, Jia Yu, Yuanyuan Tian, Richard Sidle, and Ronald Barber.
SIGMOD 2019.

Fast Failure Recovery for Main-Memory DBMSs on Multicores. [paper]
Yingjun Wu, Wentian Guo, Chee-Yong Chan, and Kian-Lee Tan.
SIGMOD 2017.

An Empirical Evaluation of In-Memory Multi-Version Concurrency Control. [paper]
Yingjun Wu, Joy Arulraj, Jiexi Lin, Ran Xian, and Andrew Pavlo.
VLDB 2017.

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.
CIDR 2017.

Transaction Healing: Scaling Optimistic Concurrency Control on Multicores. [paper]
Yingjun Wu, Chee-Yong Chan, and Kian-Lee Tan.
SIGMOD 2016.

Scalable In-Memory Transaction Processing with HTM. [paper] [website]
Yingjun Wu and Kian-Lee Tan.
USENIX ATC 2016.

ChronoStream: Elastic Stateful Stream Computation in the Cloud. [paper]
Yingjun Wu and Kian-Lee Tan.
ICDE 2015.

SocialTransfer: Transferring Social Knowledge for Cold-Start Crowdsourcing. [paper]
Zhou Zhao, James Cheng, Furu Wei, Ming Zhou, Wilfred Ng, and Yingjun Wu.
CIKM 2014.

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.
CloudCom 2012.

Invited Talks

A Deep Dive into the Compaction for Log-Structured Storage.
IBM Almaden Research Center, San Jose, CA, USA, July 2018.

Building an Efficient Index Structure for Modern Database Systems.
IBM Almaden Research Center, San Jose, CA, USA, June 2018.

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.

Awards

Manager's Choice Award, IBM Almaden Research Center.

Dean's Graduate Research Award, National University of Singapore.

Excellent Graduate Thesis Award, South China University of Technology.

Services

General/Program Chair: AIDB Workshop@VLDB 2019/2020/2021, SMDB Workshop@ICDE 2020/2021/2022, DEBS 2022 (Industrial).

Program Committee: SIGMOD 2018 (Demo), ICDE 2018 (Demo), EuroSys 2018 (Shadow), VLDB 2019, VLDB 2019 (PhD Workshop), IEEE Big Data 2019 (Industrial), VLDB 2020, ICDE 2021, SIGMOD 2021 (Reproducibility), VLDB 2021 (Demo), ICDE 2022, SIGMOD 2022 (Reproducibility), VLDB 2022 (Industrial).

Journal Reviewer: JCST, KAIS, TCC, TKDE, TPDS, VLDBJ, TODS.

Teaching

CS3103: Computer Networks and Protocols.
National University of Singapore, 2014-2015.





Last update: Sep. 2022