Education

• Doctor of Philosophy in Computer Science, The University of Western Australia, 2022-current
• Bachelor of Science in Computer Science (Honour), The University of Western Australia, 2021-2021
• Master of Information Technology, The University of Western Australia, 2016-2017
• Bachelor of Engineering in Nuclear Engineering and Technology, North China Electric Power University, 2011-2015

Awards

• Best Demo Paper Award at EMNLP, 2024
• STUDENTS CHOICE AWARD FOR ACADEMIC OR PROFESSIONAL STAFF PROGRAMS THAT ENHANCE LEARNING, 2023
• Best Research Paper Award at AusDM, 2022
• Finalist for the 31st INCITE Awards (Research & Innovation Project of the Year), 2022
• 2021-2022 Finalist for ACS WA Dennis Moore 1962 Prize, 2022

Work experience

• Full Stack Developer, Artrya, 2021-2023
  • Lead the re-architecture of the AI based coronary artery disease evaluation platform, Salix
  • Get the whole platform ready for commercial launch
• Full Stack Developer, MetroCount, 2019-2021
  • Develop and successfully commercialize the revolutionary traffic data management platform, ATLYST
  • And the revolutionary Real-Time traffic data collection solution, RoadPod VM
• Full Stack Developer, Sheda, 2018-2019
  • Support the development of several startup projects
  • HealthDelivered: A platform for dietitians to manage their patients
  • Jean: Posts (images and text) generation used for Facebook pages admin

Publications

OpenOmni: A Collaborative Open Source Tool for Building Future-Ready Multimodal Conversational Agents

[OpenOmni: A Collaborative Open Source Tool for Building Future-Ready Multimodal Conversational Agents](https://aclanthology.org/2024.emnlp-demo.5) (Sun et al., EMNLP 2024)

Docs2KG: Unified Knowledge Graph Construction from Heterogeneous Documents Assisted by Large Language Models

Sun, Q., Luo, Y., Zhang, W., Li, S., Li, J., Niu, K., Kong, X., & Liu, W. Docs2KG: Unified Knowledge Graph Construction from Heterogeneous Documents Assisted by Large Language Models. arXiv:2406.02962 [cs.CL].

Are Graph Embeddings the Panacea?

Sun, Q., Huynh, D.Q., Reynolds, M., Liu, W. (2024). Are Graph Embeddings the Panacea?. In: Yang, DN., Xie, X., Tseng, V.S., Pei, J., Huang, JW., Lin, J.CW. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2024. Lecture Notes in Computer Science(), vol 14646. Springer, Singapore. https://doi.org/10.1007/978-981-97-2253-2_32

Graph Embeddings for Non-IID Data Feature Representation Learning

Sun, Q., Liu, W., Huynh, D., Reynolds, M. (2022). Graph Embeddings for Non-IID Data Feature Representation Learning. In: Park, L.A.F., et al. Data Mining. AusDM 2022. Communications in Computer and Information Science, vol 1741. Springer, Singapore. https://doi.org/10.1007/978-981-19-8746-5_4