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Professor Gill Dobbie


Gill worked in industry for a couple of years before she became an academic. She has held permanent and visiting positions at the University of Melbourne, Victoria University of Wellington and the National University of Singapore.

Research | Current

Gill has a wide range of research interests, including databases, the web, and software engineering.

She is interested both in structured and semistructured data. More specifically, she is interested in how data can best be organized and managed, how the semantics of the data can be retained and expressed, and how querying can be carried out efficiently.

Her main areas of interest pertain to databases and the web. She has worked in the foundations of database systems, defining logical models for various kinds of database systems, and reasoning about the correctness of algorithms in that setting. With colleagues at the National University of Singapore, she has defined a data model for semistructured data (called ORA-SS), providing a language independent description of the data. The group she was working with has used the ORA-SS data model to define a normal form for ORA-SS schema, defined valid views for semistructured databases, and described a storage structure for semistructured databases using object relational databases.

Selected publications and creative works (Research Outputs)

  • Zhang, S., Jung Huang, D. T., Dobbie, G., & Koh, Y. S. (2020). SLED: Semi-supervised locally-weighted ensemble detector. Proceedings - International Conference on Data Engineering. 10.1109/ICDE48307.2020.00183
    Other University of Auckland co-authors: Yun Sing Koh
  • Zhuo, S., Sherlock, L., Dobbie, G., Koh, Y. S., Russello, G., & Lottridge, D. (2020). REAL-Time Smartphone Activity Classification Using Inertial Sensors-Recognition of Scrolling, Typing, and Watching Videos While Sitting or Walking. Sensors (Basel, Switzerland), 20 (3).10.3390/s20030655
    Other University of Auckland co-authors: Yun Sing Koh, Giovanni Russello, Danielle Lottridge
  • Wu, O., Koh, Y. S., Dobbie, G., & Lacombe, T. (2020). PEARL: Probabilistic Exact Adaptive Random Forest with Lossy Counting for Data Streams. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10.1007/978-3-030-47436-2_2
    Other University of Auckland co-authors: Ocean Wu, Yun Sing Koh
  • Anderson, R., Koh, Y. S., Dobbie, G., & Bifet, A. (2019). Recurring concept meta-learning for evolving data streams. EXPERT SYSTEMS WITH APPLICATIONS, 13810.1016/j.eswa.2019.112832
    Other University of Auckland co-authors: Yun Sing Koh
  • Cai, C.-H., Sun, J., & Dobbie, G. (2019). Automatic B-model repair using model checking and machine learning. AUTOMATED SOFTWARE ENGINEERING, 26 (3), 653-704. 10.1007/s10515-019-00264-4
    Other University of Auckland co-authors: Jing Sun
  • Algawiaz, D., Dobbie, G., & Alam, S. (2019). PRARS: Risk assessment model for recommender systems. Frontiers in Artificial Intelligence and Applications. 10.3233/FAIA190091
  • Bian, R., Koh, Y. S., Dobbie, G., & Divoli, A. (2019). Identifying Top-k Nodes in Social Networks: A Survey. ACM COMPUTING SURVEYS, 52 (1)10.1145/3301286
    Other University of Auckland co-authors: Yun Sing Koh
  • Cai, C.-H., Sun, J., Dobbie, G., & Lee, S. U.-J. (2019). Achieving Abstract Machine Reachability with Learning-based Model Fulfilment. Paper presented at 26th Asia-Pacific Software Engineering Conference (APSEC), Putrajaya, MALAYSIA. 2 December - 5 December 2019. 2019 26TH ASIA-PACIFIC SOFTWARE ENGINEERING CONFERENCE (APSEC). (pp. 8). 10.1109/APSEC48747.2019.00043
    Other University of Auckland co-authors: Jing Sun


Contact details

Primary office location

SCIENCE CENTRE 303 - Bldg 303
Level 5, Room 519
New Zealand

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