Dave Tran, PhD

Vietnamese: Đại Hoàng Trần
AI Engineer at Oracle
Dave Tran received BS degree in Information Technology from Fontys University of Applied Science in Eindhoven, Netherlands and MSc degree in Computing Engineering from Kyung Hee University, Korea, in Computer Science, in 2011 and 2015, respectively. He also works in the industry for more than 5 years as a software developer for several companies. The work varies from providing customized web services to making mobile apps for specific needs. Since Dec-2017, he got iMQRTP scholarship to follow up with PhD degree in Macquarie University , under supervision of Professor Michael Sheng. His research interest was applying analytic techniques of deep learning to tackle recommender systems and NLP challenges.

In 2021, Dave joined Oracle as an Artificial Intelligence (AI) Engineer in Oracle Digital Assistant (ODA) team.

  • Feb-2021: Joined Oracle as an AI Engineer in Oracle Digital Assistant team.
  • March-2019: Internship at BeeCastle to build a customized Recommender System for Next-Best-Action
  • Dec-2018: Guest Speaker at Sioux Asia in Da Nang about Artificial Intelligence and Deep Learning info
  • Nov-2018: My poster entitled, 'Auto Layout for Recommender System using GAN', has been awarded 'Best Poster Award' at the Macquarie University's Computing Industry Networking Event. Download
  • Nov-2018: My thesis 'Graph-based Recommender System using Deep Learning' has been approved for Confimration of PhD Candidature

  • Awards
  • 2021: PhD of Computer Science (Macquarie University) awarded
  • 2018: CSIRO Data61 Scholarship Award info
  • 2018: Entrepreneurial Enrichment PhD Program Award: info
  • 2017: Macquarie MQRTP HDR Award: info
  • 2013: Kyung Hee University Master Degree Scholarship Award: info
  • 2010: HSP Huygens Scholarship Award: info

  • Publications

    • [2020] Dai Hoang Tran, Abdulwahab Aljubairy, Munazza Zaib, Quan Z. Sheng, Wei Emma Zhang, Nguyen H. Tran and Khoa L.D. Nguyen, “HeteGraph: A Convolutional Framework for Graph Learning in Recommender Systems”, IJCNN 2020, July 2020. PDF
    • [2020] Dai Hoang Tran, Quan Z. Sheng, Wei Emma Zhang, Salma Abdalla Hamad, Munazza Zaib, Nguyen H. Tran, Lina Yao, Nguyen Lu Dang Khoa, “Deep Conversational Recommender Systems: A New Frontier for Goal-Oriented Dialogue Systems”, arXiv, May 2020. PDF
    • [2018] Dai Hoang Tran, Zawar Hussain, Wei Zhang, Khoa L.D. Nguyen, Nguyen H. Tran and Quan Z. Sheng, “Deep Autoencoder for Recommender Systems: Parameter Influence Analysis”, ACIS 2018, Dec. 2018. PDF
    • [1] D. H. Tran, N. H. Tran, C. Pham, S. M. A. Kazmi, E.-N. Huh, and C. S. Hong, “OaaS: offload as a service in fog networks,” Computing, vol. 99, no. 11, pp. 1081–1104, Nov. 2017. PDF
    • [2] N. H. Tran, D. H. Tran, S. Ren, Z. Han, E. N. Huh, and C. S. Hong, “How Geo-Distributed Data Centers Do Demand Response: A Game-Theoretic Approach,” IEEE Transactions on Smart Grid, vol. 7, no. 2, pp. 937–947, Mar. 2016. PDF
    • [3] D. H. Tran et al., “HiLiCLoud: High performance and lightweight mobile cloud infrastructure for monitor and benchmark services,” in 2015 17th Asia-Pacific Network Operations and Management Symposium (APNOMS), 2015, pp. 416–419. PDF
    • [4] C. T. Do, N. H. Tran, D. H. Tran, C. Pham, M. G. R. Alam, and C. S. Hong, “Toward service selection game in a heterogeneous market cloud computing,” in 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM), 2015, pp. 44–52. PDF
    • [5] C. Pham, H. D. Tran, S. I. Moon, K. Thar, and C. S. Hong, “A general and practical consolidation framework in CloudNFV,” in 2015 International Conference on Information Networking (ICOIN), 2015, pp. 295–300. PDF
    • [6] N. H. Tran, D. H. Tran, L. B. Le, Z. Han, and C. S. Hong, “Load balancing and pricing for spectrum access control in cognitive radio networks,” in 2014 IEEE Global Communications Conference, 2014, pp. 1035–1040. PDF
    • [7] D. H. Tran, T. D. Nguyen, E. N. Huh, and C. S. Hong, “A performance comparison of in-memory Virtual Desktop Environment,” in The 16th Asia-Pacific Network Operations and Management Symposium, 2014, pp. 1–4. PDF

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