Hong Gunn Chew

Research Interests

Autonomous Vehicles Computer Software Computer System Security Electrical and Electronic Engineering Knowledge Representation and Machine Learning

Dr Hong Gunn Chew

Lecturer

School of Electrical and Mechanical Engineering

College of Engineering and Information Technology

Eligible to supervise Masters and PhD - email supervisor to discuss availability.

Hong Gunn is a Lecturer 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.

Date Position Institution name
2023 - 2025 Associate Head of Learning and Teaching (operation) University of Adelaide
2020 - ongoing Lecturer University of Adelaide
2017 - 2019 Associate Lecturer University of Adelaide, Adelaide
2013 - 2017 Teaching Laboratories Manager The University of Adelaide
2012 - 2013 Casual Associate Lecturer (Practical Coordinator) University of Adelaide, Adelaide

Date Type Title Institution Name Country Amount
2016 Teaching Award ECMS Faculty Prize for Excellence in Professional Support of Learning & Teaching University of Adelaide Australia $1000

Language Competency
Chinese (Mandarin) Can speak and understand spoken
English Can read, write, speak, understand spoken and peer review

Date Institution name Country Title
2013 University of Adelaide, Adelaide Australia Ph.D
1995 University of Tasmania, Hobart Australia B.E., B.Sc.

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 Scopus6 WoS5

Year Citation
2026 Simpson, L., Millar, K., Cheng, A., Lim, C. C., & Chew, H. G. (2026). Graph-Based Integrated Gradients for Explaining Graph Neural Networks. In Lecture Notes in Computer Science (Vol. 16370 LNAI, pp. 150-162). Springer Nature Singapore.
DOI
2026 Simpson, L., Millar, K., Cheng, A., Lim, C. C., & Chew, H. G. (2026). Probabilistic Lipschitzness and the Stable Rank for Measuring XAI Model Robustness. In Lecture Notes in Computer Science (Vol. 16370 LNAI, pp. 137-149). Springer Nature Singapore.
DOI
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 Scopus19
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 WoS9

Year Citation
2024 Simpson, L., Costanza, F., Millar, K., Cheng, A., Lim, C. C., & Chew, H. G. (2024). Algebraic Adversarial Attacks on Integrated Gradients. In Proceedings - International Conference on Machine Learning and Cybernetics (pp. 26-31). Hybrid, Miyazaki: IEEE.
DOI Scopus1
2024 Simpson, L., Costanza, F., Millar, K., Cheng, A., Lim, C. C., & Chew, H. G. (2024). Tangentially Aligned Integrated Gradients for User-Friendly Explanations. In CEUR Workshop Proceedings Vol. 3910 (pp. 1-12). Dublin, Ireland: CEUR-WS.
Scopus1
2023 Simpson, L., Millar, K., Cheng, A., Chew, H. G., & Lim, C. C. (2023). A Testbed for Automating and Analysing Mobile Devices and Their Applications. In Proceedings - International Conference on Machine Learning and Cybernetics (pp. 201-208). Online: IEEE.
DOI Scopus1
2023 Robertson, W., Yung, W. K., Hall, H., Chew, H. G., & Missingham, D. (2023). Honours project marking of seminar and expo assessments with a robust statistical approach. In Proceedings of the 34th Australasian Association for Engineering Education Annual Conference (AAEE), 2023 Vol. 2024 (pp. 1-9). Online: Australasian Association for Engineering Education.
DOI Scopus7 WoS3
2022 Millar, K., Simpson, L., Cheng, A., Chew, H. G., & Lim, C. (2022). Detecting Botnet Victims Through Graph-Based Machine Learning. In 2021 International Conference on Machine Learning and Cybernetics (ICMLC) Vol. 2021-December (pp. 6 pages). online: IEEE.
DOI Scopus3
2022 Millar, K., Cheng, A., Chew, H. G., & Lim, C. (2022). Clustering Network-Connected Devices Using Affiliation Graphs. In 2021 International Conference on Machine Learning and Cybernetics (ICMLC) Vol. 2021 December (pp. 7 pages). online: IEEE.
DOI Scopus2
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 Scopus3 WoS1
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 Scopus12
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 Scopus14 WoS12
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 Scopus12 WoS5
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). UT, SALT LAKE CITY: IEEE.
DOI Scopus76 WoS42
2001 Chew, H., Bogner, R. E., & 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.

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).

Year Citation
2025 Simpson, L., Costanza, F., Millar, K., Cheng, A., Lim, C. -C., & Chew, H. G. (2025). Algebraic Adversarial Attacks on Explainability Models.
2025 Simpson, L., Costanza, F., Millar, K., Cheng, A., Lim, C. -C., & Chew, H. G. (2025). Tangentially Aligned Integrated Gradients for User-Friendly Explanations.
2024 Simpson, L., Costanza, F., Millar, K., Cheng, A., Lim, C. -C., & Chew, H. G. (2024). Algebraic Adversarial Attacks on Integrated Gradients.
2024 Simpson, L., Millar, K., Cheng, A., Lim, C. -C., & Chew, H. G. (2024). Probabilistic Lipschitzness and the Stable Rank for Comparing
Explanation Models.
2023 Simpson, L., Millar, K., Cheng, A., Chew, H. G., & Lim, C. -C. (2023). A Testbed for Automating and Analysing Mobile Devices and their
Applications.
  • “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.

Course coordinator and lecturer of these courses

Level Course Year
III Computer Architecture 2023-
III Research Methods and Project Management 2021-2022
III Project Management 2019-2020

 

Lecturer of these courses:

Level Course Year
I Digital Electronics 2021-

 

Practical coordinator of these courses:

Level Course Years
I EEE IA 2012-2015
  EEE IB 2012-2016
  Analogue Electronics 2016-
  Electronic Systems 2016-
  Digital Electronics 2021-
II Electronics 2023-

2012-2016
  Circuit & Systems 2023-
  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 2012-2019
III Project Management 2016-2020
IV/PG Distributed Generation Tech 2012-

 

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

Level Course Year
IV Design Project (EEE) 2013-2014
  Honours Project (EEE) 2013-2021
  Honours Project (Engineering)

co-coordinator		 2022-
PG Masters Project (SIP) 2013-2016
  Masters Project (Electronic) 2013-
  Masters Project (Electrical) 2013-
  Masters Project (Engineering) 2020-

 

Date Role Research Topic Program Degree Type Student Load Student Name
2022 Co-Supervisor Characterisation of devices within private and encrypted networks Doctor of Philosophy Doctorate Full Time Mr Lachlan Connor Simpson
2022 Co-Supervisor Characterisation of devices within private and encrypted networks Doctor of Philosophy Doctorate Full Time Mr Lachlan Connor Simpson

Date Role Research Topic Program Degree Type Student Load Student Name
2018 - 2022 Co-Supervisor Graph-Based Machine Learning for Passive Network Reconnaissance within Encrypted Networks Doctor of Philosophy Doctorate Part Time Mr Kyle Alexander Millar

Date Role Committee Institution Country
2025 - 2026 Treasurer IEEE South Australia Section IEEE United States
2025 - ongoing Secretary IEEE Computer Society South Australia chapter IEEE Australia
2023 - ongoing Member School Advisory Board (EME) The University of Adelaide Australia
2022 - ongoing Member SET Faculty HSW Committee The University of Adelaide Australia
2021 - 2024 Treasurer IEEE Computer Society South Australia chapter IEEE Australia
2019 - 2022 Member ECMS Faculty HSW Committee The University of Adelaide Australia
2013 - 2021 Member School Advisory Committee University of Adelaide Australia

Date Role Membership Country
2019 - ongoing Member Australasian Association for Engineering Education Australia
1999 - ongoing Member Institute of Electrical and Electronic Engineers United States
1999 - ongoing Member IEEE United States

Date Office Name Institution Country
2019 - ongoing Health and Safety Representative The University of Adelaide Australia
2002 - 2003 Treasurer - Computer Society SA chapter IEEE United States

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