Hong Gunn Chew

Dr Hong Gunn Chew

Lecturer

School of Electrical and Electronic Engineering

Faculty of Engineering, Computer and Mathematical Sciences

Eligible to supervise Masters and PhD (as Co-Supervisor) - email supervisor to discuss availability.


Hong Gunn is a Teaching Fellow with the School of Electrical and Electronic Engineering. He is the electronics practical coordinator and final year projects coordinator in the school. His research interest are in Machine Learning, Autonomous Systems, Cyber Security and Energy Management.

My research interest are in Machine Learning, Autonomous Systems, Cyber Security and Energy Management.

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  • Journals

    Year Citation
    2009 Chew, H., & Lim, C. (2009). On regularisation parameter transformation of support vector machines. Journal of Industrial and Management Optimization, 5(2), 403-415.
    DOI Scopus5 WoS4
  • Book Chapters

    Year Citation
    2019 Millar, K., Cheng, A., Chew, H. G., & Lim, C. C. (2019). Using convolutional neural networks for classifying malicious network traffic. In M. Alazab, & M. Tang (Eds.), Deep Learning Applications for Cyber Security (pp. 103-126). Cham, Switzerland: Springer Nature.
    DOI Scopus5
    2005 Chew, H., Lim, C., & Bogner, R. (2005). An implementation of training dual-nu support vector machines. In L. Qi, K. Teo, & X. Yang (Eds.), Applied optimization - Optimization and control with applications (Vol. 96, pp. 157-182). New York, USA: Springer.
    DOI WoS8
  • Conference Papers

    Year Citation
    2020 Millar, K. A., Cheng, A., Chew, H. G., & Lim, C. C. (2020). Characterising Network-Connected Devices Using Affiliation Graphs. In IEEE/IFIP Network Operations and Management Symposium (pp. 1-6). online: IEEE.
    DOI Scopus1
    2020 Millar, K., Cheng, A., Chew, H., & Lim, C. C. (2020). Operating System Classification: A Minimalist Approach. In 2020 IEEE International Conference on Machine Learning and Cybernetics (ICMLC) Vol. 2020-December (pp. 143-150). online: IEEE.
    DOI
    2018 Millar, K. A., Cheng, A., Chew, H. G., & Lim, C. C. (2018). Deep learning for classifying malicious network traffic. In Proceedings of the 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2018), as published in Trends and Applications in Knowledge Discovery and Data Mining Vol. 11154 (pp. 156-161). Switzerland: Springer.
    DOI Scopus4
    2017 Millar, K., Smit, D., Page, C., Cheng, A., Chew, H., & Lim, C. (2017). Looking deeper: Using deep learning to identify internet communications traffic. In Proceedings of the 2017 Australasian Conference of Undergraduate Research, as published in Macquarie Matrix: Special edition, ACUR 2017 Vol. 6.1 (pp. 124-144). Adelaide, Australia: Macquarie University.
    2016 Young, B., Ertugrul, N., & Chew, H. (2016). Overview of optimal energy management for nanogrids (end-users with renewables and storage). In Proceedings of the 2016 Australasian Universities Power Engineering Conference, AUPEC 2016 (pp. 6 pages). Brisbane, AUSTRALIA: IEEE.
    DOI Scopus5 WoS1
    2004 Chew, H., Lim, C., & Bogner, R. (2004). Dual-nu support vector machines and applications in multi-class image recognition. In A. Rubinov, & M. Sniedovich (Eds.), Proceedings of the 6th International Conference on Optimization: Techniques and Applications 2004 (pp. CD-ROM 1-CD-ROM 11). CD-ROM: University of Ballarat.
    2001 Chew, H., Lim, C., & Bogner, R. (2001). On initialising nu-Support Vector Machine Training. In D. Li (Ed.), Proceedings of the 5th International Conference on Optimization: Techniques and Applications (pp. 1740-1747). HONG KONG: ICOTA.
    2001 Chew, H., Bogner, R., & Lim, C. (2001). Dual v-support vector machine with error rate and training size biasing. In V. John Matthews (Ed.), Proceedings of IEEE Signal Processing Society International Conference on Acoustics, Speech, and Signal Processing 2001 (pp. CDROM 1-CDROM 4). CD-ROM: IEEE SIGNAL PROCESSING SOCIETY.
    DOI
    2001 Chew, H. G., Bogner, R. E., & Lim, C. C. (2001). Dual ν-support vector machine with error rate and training size biasing. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings Vol. 2 (pp. 1269-1272). SALT LAKE CITY, UT: IEEE.
    DOI Scopus67 WoS34
    2001 Chew, H., Bogner, R., & Lim, C. (2001). Dual nu-support vector machine with error rate and training size biasing. In 2001 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS I-VI, PROCEEDINGS (pp. 4041). SALT LAKE CITY, UT: IEEE.
    2000 Chew, H., Crisp, D., Bogner, R., & Lim, C. (2000). Target detection in radar imagery using support vector machines with training size biasing. In J. Wang (Ed.), Proceedings of ICARCV 2000 - Sixth International Conference on Control, Automation, Robotics and Vision (pp. CD). Singapore: School of Electrical & Electronic Engineering, NTU.
  • Theses

    Year Citation
    2013 Chew, H. G. (2013). Support Vector Machines with Dual Error Extensions for Target Detection and Object Recognition. (PhD Thesis, The University of Adelaide).
  • “Eavesdropping and malicious/deceptive jammer detection using machine learning in wireless sensor networks”, South Korean Agency for Defense Development, $191k, August 2014 – August 2017, 0.10 FTE contribution.
  • “Swarm Intelligence and Multi-Mission Coordination in Urban Areas”, Defence Science and Technology Group, $99.9k, March 2017 – August 2018, 0.05 FTE contribution.
  • “Swarm Intelligence and Genetic Fuzzy Trees for Threat Avoidance and Target Allocation”, Defence Science and Technology Group, $99.9k, March 2017 – August 2018, 0.05 FTE contribution.

Practical coordinator of these courses:

Level Course Years
I EEE IA 2012-2015
  EEE IB 2012-2016
  Analogue Electronics 2016-
  Electronic Systems 2016-
II Electronics 2012-2016
  Circuit Analysis 2012-2016
  Signal and Systems 2012-2016
  Engineering Electromagnetics 2012-
  Electronic Circuits 2017-
  Electronic Circuits M 2016-
III/PG RF Engineering 2012-
  Control 2012-
III Project Management 2016-
IV/PG Distributed Generation Tech 2012-

 

Course coordinator of Final Year Projects for Undergraduates (Honours) and Postgraduates (Masters)

Level Course Year
IV Design Project 2013-2014
  Honours Project 2013-
PG Masters Project (SIP) 2013-2016
  Masters Project (Electronic) 2013-
  Masters Project (Electrical) 2013-
  Masters Project (Engineering) 2020-

 

Course coordinator and lecturer of these courses

Level Course Year
III Project Management 2019-2020
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  • Other Supervision Activities

    Date Role Research Topic Location Program Supervision Type Student Load Student Name
    2018 - ongoing Co-Supervisor Classifying Network Connected Devices and Applications using Deep Learning The University of Adelaide Doctorate Full Time Kyle Millar
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  • Committee Memberships

    Date Role Committee Institution Country
    2021 - ongoing Treasurer IEEE Computer Society South Australia chapter IEEE Australia
    2013 - ongoing Member School Advisory Committee University of Adelaide Australia
  • Memberships

    Date Role Membership Country
    1999 - ongoing Member Institute of Electrical and Electronic Engineers United States
  • Offices Held

    Date Office Name Institution Country
    2002 - 2003 Treasurer IEEE - Computer Society SA chapter Australia
  • Position: Lecturer
  • Phone: 83131641
  • Email: honggunn.chew@adelaide.edu.au
  • Campus: North Terrace
  • Building: Ingkarni Wardli, floor 3
  • Room: 3 52
  • Org Unit: School of Electrical and Electronic Engineering

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