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Phung, Son Lam. Associate Professor

Associate Professor

  • Faculty of Engineering and Information Sciences
  • School of Electrical, Computer and Telecommunications Engineering
  • Signals, Information and Communications Research Institute (SICOM)
  • Acting Coordinator - Centre for Signal and Information Processing (CSIP)

Overview


I received B. Eng. with first-class honours and Ph.D. in computer engineering, from Edith Cowan University, Perth, Australia. I was awarded the University Medal in 2000 as the graduating student with the highest course average. 


I have been a Chief Investigator for three ARC Discovery Projects, three Defence Innovation Network Pilot Projects, one Defence Innovation Network PhD Project, and one Qatar National Research Fund grant. I have co-supervised to successful completion 23 HDR students (15 PhD and 8 MPhil), and received Research Paper Awards at 5 international conferences (ICASSP-2016, DICTA-2014, EUVIP-2010, AVSS-2009, ANZIIS-2001).

I also received  the Highly Commended Supervisor Award at the 2012 Canon Extreme Imaging Competition and the OCTAL Faculty Early Career teaching award in 2010.

At UOW, I currently serve as Member of the UOW Thesis Examination CommitteeResearch Sub-cluster Representative for Electrical/Electronic Engineering (0906), Member of EIS Faculty Research Committee and SECTE School Research Committee.

Top Publications


Research Overview


  • My research is in the areas of image processing, pattern recognition, signal processing, machine learning and artificial intelligence. I focus on developing new algorithms and systems to solve strategic and practical problems in defence, security, healthcare, and industry. 

    I have published over 110 Scopus-listed papers in international journals and conferences. Several publications appear in high-impact journals, including IEEE Trans. Neural Networks and Learning Systems, IEEE. Trans. Image Processing, Pattern Recognition, IEEE. Trans. Signal Processing, IEEE Trans. Pattern Analysis and Machine Intelligence, IEEE Trans. Geoscience and Remote Sensing. My papers have received over 1970 Scopus citations (h-index: 20), and over 3420 Google Scholar citations (h-index: 26).

    Among several research projects, I and my team are currently developing assistive navigation tools for vision-impaired people, sonar image processing algorithms for underwater mine detection, and through-wall radar imaging. I am mentoring a group of highly motivated, hard-working and capable research students.

    I conduct research in the Centre for Signal and Information Processing (CSIP) at the Signals, Information and Communications Research Institute (SICOM). I have been a Conference Organizing Committee member for 3 international conferences, and a peer reviewer for numerous high-impact journals and conferences.

Available as Research Supervisor

Available for Collaborative Projects

Member Of


  • IEEE Senior Member 2014 -

Selected Publications


Investigator On


Other Research Activities


Impact Story


  • <p>Underwater mines are a cost-effective tool in asymmetric warfare and are commonly used to block shipping lanes and restrict naval operations. The aim of this research is develop an automatic system based on sonar imaging for locating naval mines and then recognizing their various types. It involves investigating the latest advances in deep learning and artificial intelligence for object detection, image segmentation, and image classification.<br /><br />This on-going research, supported by the <em>NSW Defence Innovation Network </em>(DIN), is conducted in collaboration with <em>Defence and Science Technology Group</em> (DSTG) and a defence software company. The research team includes Assoc. Prof. Son Lam Phung (<em>CI, Technical Lead, Principal Supervisor</em>), Mr Hoang Thanh Le (PhD Student), Mr Luca Russo (PhD student), Dr. Thi N. A. Nguyen (Associate Research Fellow), Senior Prof. Salim Bouzerdoum (CI), Prof. Christian Ritz (CI), and Dr. Le Chung Tran (CI).<br /><br />In this project, we have developed a deep learning-based tool for underwater mine detection. Further discussions are in progress to apply the project outcomes. </p><p><strong>Publication</strong>: H. T. Le, S. L. Phung, P. B. Chapple, A. Bouzerdoum, C. H. Ritz, L. C. Tran, "Deep Gabor neural network for automatic detection of mine-like objects in sonar imagery," <em>IEEE Access</em>, vol. 8, no. 1, pp. 94126-94139, 2020.</p>
  • <p>Over 250 million people worldwide and 380,000 people in Australia suffer from visual impairment. The aim of the project is to develop, based on deep learning and artificial intelligence technologies, a portable electronic tool that enables a vision-impaired user to perform micro-navigation tasks. The targeted tasks include locating the pedestrian path in crowded scenes, evading obstacles and hazards, and recognising relevant landmarks. The technologies developed in this project can be adopted for road safety, self-driving vehicles, and autonomous robots.<br /><br />This project is funded by an ARC Discovery Project DP190100607, titled "<em>Assistive Micro-Navigation for Project for Vision Impaired People"</em> (2019-2021). It is one of five national projects highlighted in the Ministerial Media Release on 27 Nov 2018 <a href="https://www.arc.gov.au/news-publications/media/media-releases/funding-world-leading-research" target="_blank" rel="noopener">(link)</a>. The research team includes blind volunteers, Assoc. Prof. Son Lam Phung (CI), Senior Prof. Salim Bouzerdoum (CI), Dr Thi N. A. Nguyen (Associate Research Fellow), and a number of PhD/MPhil students.</p><p>This on-going research has received the <strong><em>Best Recognition Paper Award</em></strong> at the International Conference on Digital Image Computing: Techniques and Applications (DICTA) in 2014, and the <em><strong>Highly Commended Award</strong></em> at the Canon Extreme Imaging Competition in 2012. Recently, we have reached a project milestone by successfully developing a deep learning-based tool to locate the pedestrian path for the blind. This tool is published in <em>IEEE TNNLS</em> which has an impact factor of 8.793 (top 10% in 136 computer science and AI journals, and top 5% in 266 electrical/electronic engineering journals).</p><p><strong>Publication</strong>: T. N. A. Nguyen, S. L. Phung, and A. Bouzerdoum, "Hybrid deep learning-Gaussian process network for pedestrian lane detection in unstructured scenes," <em>IEEE Transactions on Neural Networks and Learning Systems, </em>2020. <a href="https://ieeexplore.ieee.org/document/8998354" target="_blank" rel="noopener">(URL)</a></p>

Available as Research Supervisor

Potential Supervision Topics


  • - image, video, and signal processing
    - assistive navigation for vision-impaired people, autonomous navigation
    - machine learning, pattern recognition, neural networks, deep learning
    - through-wall radar imaging, ground-penetrating radar, micro-Doppler radar
    - imaging applications in defence, security, and healthcare
    - magnetic resonance imaging, atomic force microscopy
    - sonar, thermal and hyperspectral imaging
    - depth sensing and 3D object scanning

Teaching Activities


Advisees


  • Graduate Advising Relationship

    Degree Research Title Advisee
    Doctor of Philosophy Deep Learning Algorithms for Image Segmentation and Generation Ang, Paul
    Doctor of Philosophy Deep Learning Algorithms for Image and Signal Processing Applications Le Hoang, Thanh
    Doctor of Philosophy Depth Perception from a Single Colour Image Thompson, Joshua
    Doctor of Philosophy Real-time Automatic Target Recognition of Naval Mines with Autonomous Underwater Vehicle Sonar Imaging Russo, Luca
    Doctor of Philosophy Depth Estimation with Deep Learning for Assistive Navigation Phan, Steve
    Doctor of Philosophy 3D Face Modelling and Recognition for Automatic Selection of Worker Respiratory Protective Equipment Nguyen, Tran Thanh Phong
    Doctor of Philosophy Scene Perception and 3D Sound Synthesis for Assistive Navigation of Blind People Lei, Yunjia
    Master of Philosophy - EIS Deep Learning for Hyperspectral Image Processing Bui, Ly

Awards And Honors


Teaching Overview


  • - UOW Outstanding Contribution to Teaching and Learning, Faculty of Informatics Early Career Award 2010.

    - Peer Recognition Teaching Award by the Australian College of Educators in 2011.

    - Peer Recognition Teaching Award by the Australian College of Educators in 2007.

    - UOW Educational Strategic Development Fund (ESDF) grant, "Integrating MATLAB-based experimentation into engineering curriculum,” Son Lam Phung, Abdesselam Bouzerdoum, Montserrat Ros, 2010, $6,000.

    - UOW ESDF grant, "Developing an immersive environment and platform for microcontroller study,” Montserrat Ros, Son Lam Phung, David Stirling, Peter Vial, Christian Ritz, 2008, $14,000.

    - UOW Educational Resource Development Agreement, ERDA Project, “Enhancing microcontroller curriculum with video resources,” 2015.

Keywords


  • image processing, machine learning, artificial intelligence, pattern recognition, signal processing, deep learning, neural networks, radar imaging, magnetic resonance imaging, atomic force microscopy, multispectral imaging, thermal imaging, mine countermeasures.

Mailing Address


  • University of Wollongong, SECTE (EIS)

    Northfields Avenue

    Wollongong

    NSW

    2522

    Australia

Top Publications


Research Overview


  • My research is in the areas of image processing, pattern recognition, signal processing, machine learning and artificial intelligence. I focus on developing new algorithms and systems to solve strategic and practical problems in defence, security, healthcare, and industry. 

    I have published over 110 Scopus-listed papers in international journals and conferences. Several publications appear in high-impact journals, including IEEE Trans. Neural Networks and Learning Systems, IEEE. Trans. Image Processing, Pattern Recognition, IEEE. Trans. Signal Processing, IEEE Trans. Pattern Analysis and Machine Intelligence, IEEE Trans. Geoscience and Remote Sensing. My papers have received over 1970 Scopus citations (h-index: 20), and over 3420 Google Scholar citations (h-index: 26).

    Among several research projects, I and my team are currently developing assistive navigation tools for vision-impaired people, sonar image processing algorithms for underwater mine detection, and through-wall radar imaging. I am mentoring a group of highly motivated, hard-working and capable research students.

    I conduct research in the Centre for Signal and Information Processing (CSIP) at the Signals, Information and Communications Research Institute (SICOM). I have been a Conference Organizing Committee member for 3 international conferences, and a peer reviewer for numerous high-impact journals and conferences.

Member Of


  • IEEE Senior Member 2014 -

Selected Publications


Investigator On


Other Research Activities


Impact Story


  • <p>Underwater mines are a cost-effective tool in asymmetric warfare and are commonly used to block shipping lanes and restrict naval operations. The aim of this research is develop an automatic system based on sonar imaging for locating naval mines and then recognizing their various types. It involves investigating the latest advances in deep learning and artificial intelligence for object detection, image segmentation, and image classification.<br /><br />This on-going research, supported by the <em>NSW Defence Innovation Network </em>(DIN), is conducted in collaboration with <em>Defence and Science Technology Group</em> (DSTG) and a defence software company. The research team includes Assoc. Prof. Son Lam Phung (<em>CI, Technical Lead, Principal Supervisor</em>), Mr Hoang Thanh Le (PhD Student), Mr Luca Russo (PhD student), Dr. Thi N. A. Nguyen (Associate Research Fellow), Senior Prof. Salim Bouzerdoum (CI), Prof. Christian Ritz (CI), and Dr. Le Chung Tran (CI).<br /><br />In this project, we have developed a deep learning-based tool for underwater mine detection. Further discussions are in progress to apply the project outcomes. </p><p><strong>Publication</strong>: H. T. Le, S. L. Phung, P. B. Chapple, A. Bouzerdoum, C. H. Ritz, L. C. Tran, "Deep Gabor neural network for automatic detection of mine-like objects in sonar imagery," <em>IEEE Access</em>, vol. 8, no. 1, pp. 94126-94139, 2020.</p>
  • <p>Over 250 million people worldwide and 380,000 people in Australia suffer from visual impairment. The aim of the project is to develop, based on deep learning and artificial intelligence technologies, a portable electronic tool that enables a vision-impaired user to perform micro-navigation tasks. The targeted tasks include locating the pedestrian path in crowded scenes, evading obstacles and hazards, and recognising relevant landmarks. The technologies developed in this project can be adopted for road safety, self-driving vehicles, and autonomous robots.<br /><br />This project is funded by an ARC Discovery Project DP190100607, titled "<em>Assistive Micro-Navigation for Project for Vision Impaired People"</em> (2019-2021). It is one of five national projects highlighted in the Ministerial Media Release on 27 Nov 2018 <a href="https://www.arc.gov.au/news-publications/media/media-releases/funding-world-leading-research" target="_blank" rel="noopener">(link)</a>. The research team includes blind volunteers, Assoc. Prof. Son Lam Phung (CI), Senior Prof. Salim Bouzerdoum (CI), Dr Thi N. A. Nguyen (Associate Research Fellow), and a number of PhD/MPhil students.</p><p>This on-going research has received the <strong><em>Best Recognition Paper Award</em></strong> at the International Conference on Digital Image Computing: Techniques and Applications (DICTA) in 2014, and the <em><strong>Highly Commended Award</strong></em> at the Canon Extreme Imaging Competition in 2012. Recently, we have reached a project milestone by successfully developing a deep learning-based tool to locate the pedestrian path for the blind. This tool is published in <em>IEEE TNNLS</em> which has an impact factor of 8.793 (top 10% in 136 computer science and AI journals, and top 5% in 266 electrical/electronic engineering journals).</p><p><strong>Publication</strong>: T. N. A. Nguyen, S. L. Phung, and A. Bouzerdoum, "Hybrid deep learning-Gaussian process network for pedestrian lane detection in unstructured scenes," <em>IEEE Transactions on Neural Networks and Learning Systems, </em>2020. <a href="https://ieeexplore.ieee.org/document/8998354" target="_blank" rel="noopener">(URL)</a></p>

Potential Supervision Topics


  • - image, video, and signal processing
    - assistive navigation for vision-impaired people, autonomous navigation
    - machine learning, pattern recognition, neural networks, deep learning
    - through-wall radar imaging, ground-penetrating radar, micro-Doppler radar
    - imaging applications in defence, security, and healthcare
    - magnetic resonance imaging, atomic force microscopy
    - sonar, thermal and hyperspectral imaging
    - depth sensing and 3D object scanning

Teaching Activities


Advisees


  • Graduate Advising Relationship

    Degree Research Title Advisee
    Doctor of Philosophy Deep Learning Algorithms for Image Segmentation and Generation Ang, Paul
    Doctor of Philosophy Deep Learning Algorithms for Image and Signal Processing Applications Le Hoang, Thanh
    Doctor of Philosophy Depth Perception from a Single Colour Image Thompson, Joshua
    Doctor of Philosophy Real-time Automatic Target Recognition of Naval Mines with Autonomous Underwater Vehicle Sonar Imaging Russo, Luca
    Doctor of Philosophy Depth Estimation with Deep Learning for Assistive Navigation Phan, Steve
    Doctor of Philosophy 3D Face Modelling and Recognition for Automatic Selection of Worker Respiratory Protective Equipment Nguyen, Tran Thanh Phong
    Doctor of Philosophy Scene Perception and 3D Sound Synthesis for Assistive Navigation of Blind People Lei, Yunjia
    Master of Philosophy - EIS Deep Learning for Hyperspectral Image Processing Bui, Ly

Awards And Honors


Teaching Overview


  • - UOW Outstanding Contribution to Teaching and Learning, Faculty of Informatics Early Career Award 2010.

    - Peer Recognition Teaching Award by the Australian College of Educators in 2011.

    - Peer Recognition Teaching Award by the Australian College of Educators in 2007.

    - UOW Educational Strategic Development Fund (ESDF) grant, "Integrating MATLAB-based experimentation into engineering curriculum,” Son Lam Phung, Abdesselam Bouzerdoum, Montserrat Ros, 2010, $6,000.

    - UOW ESDF grant, "Developing an immersive environment and platform for microcontroller study,” Montserrat Ros, Son Lam Phung, David Stirling, Peter Vial, Christian Ritz, 2008, $14,000.

    - UOW Educational Resource Development Agreement, ERDA Project, “Enhancing microcontroller curriculum with video resources,” 2015.

Keywords


  • image processing, machine learning, artificial intelligence, pattern recognition, signal processing, deep learning, neural networks, radar imaging, magnetic resonance imaging, atomic force microscopy, multispectral imaging, thermal imaging, mine countermeasures.

Mailing Address


  • University of Wollongong, SECTE (EIS)

    Northfields Avenue

    Wollongong

    NSW

    2522

    Australia

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