Cuong Nguyen

Cuong Nguyen

Higher Degree by Research Candidate

HDR Student

School of Computer Science

Faculty of Engineering, Computer and Mathematical Sciences


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  • Appointments

    Date Position Institution name
    2012 - 2015 Process and equipment engineer Intel Products Vietnam
  • Language Competencies

    Language Competency
    English Can read, write, speak, understand spoken and peer review
  • Education

    Date Institution name Country Title
    2018 The University of Adelaide Australia Doctor of Philosophy in Computer Science
    2015 - 2018 The University of Adelaide Australia Master of Philosophy in Electrical and Electronic Engineering
    2010 - 2012 Portland State University United States Bachelor of Science in Mechanical Engineering
  • Certifications

    Date Title Institution name Country
    2018 Deep learning specialization Coursera United States
    2012 Fundamental of Engineering Oregon State Board of Examiner for Engineering & Land Surveying United States
  • Research Interests

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  • Journals

    Year Citation
    2021 Nguyen, L. V., Nguyen, C. C., Carneiro, G., Ebendorff-Heidepriem, H., & Warren-Smith, S. C. (2021). Sensing in the presence of strong noise by deep learning of dynamic multimode fiber interference. Photonics Research, 9(4), 109-118.
    DOI Scopus2 WoS2
    2018 Nguyen, C., Ranasinghe, D., & Al-Sarawi, S. (2018). Electret-based microgenerators under sinusoidal excitations: an analytical modeling. Smart structures and systems, 21(3), 335-347.
    DOI Scopus1
    2017 Nguyen, C., Ranasinghe, D., & Al-Sarawi. (2017). Analytical modeling and optimization of electret-based microgenerators under sinusoidal excitations. Microsystem Technologies: micro and nanosystems information storage and processing systems, 23(12), 5855-5865.
    DOI Scopus5 WoS5
  • Conference Papers

    Year Citation
    2020 Nguyen, C., Do, T. T., & Carneiro, G. (2020). Uncertainty in model-agnostic meta-learning using variational inference. In Proceedings of the IEEE Winter Conference on Applications of Computer Vision (WACV 2020) (pp. 3079-3089). online: IEEE.
    DOI Scopus2 WoS2
    2020 Maicas, G., Nguyen, C., Motlagh, F., Nascimento, J. C., & Carneiro, G. (2020). Unsupervised task design to meta-train medical image classifiers. In Proceedings of the IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020) Vol. 2020-April (pp. 1339-1342). Iowa City, Iowa, USA: IEEE.
    DOI Scopus1
    Nguyen, C., Do, T. -T., & Carneiro, G. (n.d.). Similarity of Classification Tasks.
    Nguyen, C. C., Do, T. -T., & Carneiro, G. (n.d.). Probabilistic task modelling for meta-learning.
  • Working Paper

    Year Citation
    Nguyen, C., Do, T. -T., & Carneiro, G. (n.d.). PAC-Bayes meta-learning with implicit task-specific posteriors.

Courses Coordinated

Date Course Title Institution Course Level/ Code Role
Semester 1 - 2021 Foundations of Computer Science School of Computer Science 2202/ 7202/ 7208 Tutor
Semester 2 - 2021 Foundations of Computer Science School of Computer Science 2202/ 7202/ 7208 Tutor
  • Position: HDR Student
  • Email: cuong.nguyen@adelaide.edu.au
  • Campus: North Terrace
  • Building: Australian Institute for Machine Learning, floor 2
  • Room: 2.04.02
  • Org Unit: Australian Institute for Machine Learning

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