Jiannan Wang


Jiannan Wang

Assistant Professor
School of Computing Science
Simon Fraser University

Postdoc in the AMPLab at UC Berkeley (2015)
Ph.D. at THU (2013), B.Sc. at HIT (2008)

Research Areas: Database Systems, Big Data Science

Office: TASC 1 9237
Phone: 1-778-782-4288
Email: jnwang@sfu.ca

8888 University Drive
Burnaby, BC
CANADA V5A 1S6

Open positions: If you would like to work with me on big data research in the beautiful Greater Vancouver area, please email me your resume, a copy of undergraduate/graduate transcript, and a short statement of research interests, with the following subject: [PhD/Master/Visiting Application] Name+Major+School.

Research Interests


My research focus is on developing algorithms and systems for extracting value from "dirty" data. My current research topics are:
  • Data Cleaning for Machine Learning
  • Crowdsourced Data Cleaning

News


2017/01/04
2016/11/20
Want to improve query performance for your big data systems? Please check out our recent paper on data skipping, entitled "Skipping-oriented Partitioning for Columnar Layouts.", in VLDB 2017!
2016/11/10
We are happy to announce the first release of Reprowd! Reprowd facilitates the use of crowdsourcing for Data Labeling and Active Learning. The system was recently demonstraed at HCOMP 2016 and coverd by the Reproducible Science.
2016/09/06
Welcome Pei Wang, Mohamad Dolatshah, Jinglin Peng, Mathew Teoh to our lab! Thrilled to be able to work with such a group of talented students!
2016/09/01
2016/07/15
Want to know how the ActiveClean system works? Please check out our latest paper titled "ActiveClean: Interactive Data Cleaning For Statistical Modeling" in VLDB 2016.
2016/06/30
Our ActiveClean system has won the Best Demonstration Award in the ACM SIGMOD 2016 conference. The SIGMOD attendees were excited to see that the system helps data scientists to train a more reliable machine-learning model with much less time.
2016/06/26
We gave a tutorial entitled "Data Cleaning: Overview and Emerging Challenges" in the ACM SIGMOD 2016 conference. The slides can be downloaded from here.
2016/05/11
Want to extract new insights from graph data? Please check out our paper titled "Finding Gangs in War from Signed Networks" in KDD 2016!
    

Recent Publications [DBLP] [Google Scholar]


2017

2016

2015

 

Students


Graduate Students

Undergraduate Students

Visiting Students

  • Changbo Qu

 

Teaching


 

Profressional Activities


Program Committee

  • WWW (2017)
  • SIGMOD (2017, 2016), SIGMOD Demo (2016)
  • VLDB Demo (2017)
  • HCOMP (2016)
  • ICDE/TKDE poster (2017, 2016)
  • WAIM (2016, 2015, 2014)
  • APWeb (2016)

Chairing

  • SIGMOD 2017 Registration Chair

 


  Adapted from a template by Liwen Sun.