Panel 1

About Me

I am a Professional Teaching Fellow at the Auckland ICT Graduate School, the University of Auckland. I currently manage the Centre of Excellence at the school which provides business training courses in data analytics and machine learning.

My research focuses on data mining, machine learning, data stream mining, change mining, and artificial intelligence.


Companies I have worked with or have supervised students that worked there:

  • Mozilla
  • Orion Health
  • Precision Driven Health
  • AA Insurance
  • The Warehouse Group
  • Theta Consulting
  • Compucon
  • Olympic Software
  • Freighthub
Panel 2

Publications

DBLP
Google Scholar

2018
Yun Sing Koh, David Tse Jung Huang, Chris Pearce, Gillian Dobbie:
Volatility Drift Prediction for Transactional Data Streams. ICDM 2018: 1091-1096

David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie:
Interpreting Intermittent Bugs in Mozilla Applications Using Change Angle. AusDM Industry Track 2018: 318-330

2016
David T.J. Huang and Gillian Dobbie: Precision Driven Health Context Review Report. Online. Link: precision-driven-health-context-review-report

2015
David T.J. Huang: Change Mining and Analysis for Data Streams. Thesis. URL: http://hdl.handle.net/2292/27746

David T.J. Huang, Yun Sing Koh, Gillian Dobbie: Rare Pattern Mining from Data Streams Using SRP-Tree and Its Variants. TLDKS (21): 140-160

David T.J. Huang, Yun Sing Koh, Gillian Dobbie, Albert Bifet: Drift Detection using Stream Volatility. ECML/PKDD (1): 417-432

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

David T.J. Huang, Yun Sing Koh, Gillian Dobbie, Russel Pears: Detecting Changes in Rare Patterns from Data Streams. PAKDD (2): 437-448

Timothy D. Robinson, David T.J. Huang, Yun Sing Koh, Gillian Dobbie: Drift Detector for MemoryConstrained Environments. DaWaK: 414-425

2013
David T.J. Huang, Yun Sing Koh, Gillian Dobbie, Russel Pears: Tracking Drift Types in Changing Data Streams. ADMA (1): 72-83

2012
David T.J. Huang, Yun Sing Koh, Gillian Dobbie, Russel Pears: Kernel-Tree: Mining Frequent Patterns in a Data Stream Based on Forecast Support. Australasian Conference on Artificial Intelligence: 614-625

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

Panel 3

Supervision

Current

Francis Tang – BSc (Hons) | co-supervising with Yun Sing Koh
Mingshuang Wu – MIT CS 778 – working at Compucon
Tingyu Zhang – MIT CS 778 – working at Compucon

Completed

2018
Daniel Coats – BSc (Hons) | co-supervised with Gill Dobbie | Top BSc (Hons) of 2018
Josue Espinosa – CS 380 | co-supervised with Gill Dobbie
Mingxuan Liu – MIT CS 778 – worked at UoA ITS
Wilson Wu – MIT CS 778 – worked at Freighthub
Xin Chen – MIT CS 778 – worked at UoA ITS
Gautam Kumar – MIT CS 778 – worked at The Warehouse Group
Yueyuan Tan – MIT CS 778 – worked at Compucon

2017
Rose McColl – MIT CS 778 – worked at Theta | Callaghan Careers Grant | Top MIT of 2017
Alisha Thakker – MIT CS 778 – worked at Theta
Madhura Santhapadavu – MIT CS 778
Akshar Vijay – MIT CS 778

Panel 4

Contact

Dr David Tse Jung Huang
School of Computer Science
The University of Auckland
Private Bag 92019
Auckland 1142
New Zealand

Email
dtj dot huang at auckland.ac.nz