Dr David TJ Huang

Your name I recently completed my Doctor of Philosophy (PhD) in Computer Science under the supervision of Prof Gillian Dobbie and Dr Yun Sing Koh. Prior to this I studied and received my Bachelor of Science(Hons) degree in Computer Science from the University of Auckland. I also received my BSc (double major) in Chemistry and Computer Science from The University of Auckland.

Research Interest

My current research interests are in the following areas:

  • Data Stream Mining
  • Change Mining
  • Frequent/Rare Pattern Mining

Distinctions/Honours

  • Dean's List of Excellent Theses
  • Top 5 Theses Completed in the Faculty of Science 2015
  • Top 5% of Theses Completed University-Wide in 2015
  • Top Student Published Paper in Computer Science 2015

Services

  • PAKDD2016 - Publicity and Website Chair

Project

My thesis was focused on mining useful information from data streams, including tasks such as pattern mining, change detection, and volatility detection. I am specifically interested in looking at finding various stream and drift features like stream volatility (i.e. how quickly the streams change and to what extent). The discovery and usage of these features will improve the performance of current mining tasks on data streams.

Publication

David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie: Rare Pattern Mining from Data Streams using SRP-Tree and its Variants. TLDKS 2015, volume 21: 140-160

David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie, Albert Bifet: Drift Detection using Stream Volatility. ECML/PKDD 2015: 417-432

David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie, Russel Pears: Detecting Volatility Shift in Data Streams. ICDM 2014: 863-868

Timothy D. Robinson, David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie: Drift Detector for Memory-Constrained Environments. DaWaK 2014: 414-425

David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie, Russel Pears: Detecting Changes in Rare Patterns from Data Streams. PAKDD 2014: 437-448

David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie, Russel Pears: Tracking Drift Types in Changing Data Streams. ADMA 2013: 72-83

David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie, Russel Pears: Kernel-Tree: Mining Frequent Patterms in a Data Stream based on Forecast Support. Australasian Conference on Artificial Intelligence 2012: 614-625

David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie: Rare Pattern Mining on Data Streams. DaWaK 2012: 303-314

Resources

Download SEED Drift Detector (as published in IEEE ICDM 2014)

Download Change Mining and Analysis for Data Streams (Thesis)

Download ADWIN_Volatility Detector (as published in ECMLPKDD 2015)