Welcome

Tao Tang

PhD, Research Associate

STEM, University of South Australia


Biography

Tao Tang is currently pursuing his PhD degree in IT as a Henry Sutton Scholar in the Institute of Innovation, Science and Sustainability, Federation University Australia. He received the Bachelor's Degree from Chengdu College, University of Electronic Science and Technology of China in July 2019 where he won the Dean's Award. He authored/co-authored over 20 papers published in international journals and conferences (e.g., IEEE TNNLS, TFS, IoTJ, TETC, TKDE, TWEB, TNSE, ACM TOIT and WSDM ). He has served as Program Committee member of ICDM Workshop on Knowledge Graph (KG 2022). He received the Best Paper Award at the 7th IEEE International Conference on Data Science and Systems in December 2021. He is a member of ACM and IEEE, and an invited reviewer for journals such as IEEE IS, TAI, TNNLS, TCE, TCSS, TII, IoTJ, ACM CSUR, and conferences such as IEEE ICDM and ACM MM. His research interests include data science, graph learning, digital health, and responsible recommendation.

What is New:

[15/October/2024] My PhD Thesis Examination Recommendation is Passed without any requirements for amendments! I have received the completion letter from FedUni, which means I can proudly introduce myself using the title of Dr.

[29/August/2024] The paper entitled "FedGST: An Efficient Federated Graph Neural Network for Spatio-temporal PoI Recommendation" has been accepted by ACM Transactions on Sensor Networks (Q2, IF=3.9)!

[08/July/2024] I have submitted my PhD thesis entitled"Data-Efficient Graph Learning for Responsible Prediction and Recommendation" for External Examination! Good luck to me đŸ˜†

[06/June/2024] The paper entitled "Fuzzy Multi-view Graph Learning on Sparse Electronic Health Records" has been accepted by IEEE Transactions on Fuzzy Systems (Q1, IF=10.7)!

[19/March/2024] The paper entitled "Personalized Federated Graph Learning on Non-IID Electronic Health Records" has been accepted by IEEE Transactions on Neural Networks and Learning Systems (Q1, IF=10.4)!

[12/January/2024] The paper entitled "Federated Learning-based Information Leakage Risk Detection for Secure Medical Internet of Things" has been accepted by ACM Transactions on Internet Technology (Q1, IF=5.3)!

[10/January/2024] The paper entitled "Physic-Informed Explainable Continual Learning on Graphs" has been accepted by IEEE Transactions on Neural Networks and Learning Systems (Q1, IF=10.4)!

[03/November/2023] The paper entitled "Marking the Pace: A Blockchain-Enhanced Privacy-Traceable Strategy for Federated Recommender Systems" has been accepted by IEEE Internet of Things Journal (Q1, IF=10.6)!

[03/March/2023] Tao participated WSDM 2023 conference and gave an oral presentation about his research entitled "Data-Efficient Graph Learning Meets Ethics Challenges" in Singapore!

[23/November/2022] The paper entitled "Data-Efficient Graph Learning Meets Ethics Challenges" has been accepted by the 16th ACM International WSDM conference (WSDM 2023, Core: A*); Tao has also received an ACM SIGIR Student Travel Grant Award!

[September/2022] Tao was a program committee member of the ICDM workshop on Knowledge Graphs (KG 2022).

Congratulations!

[05/July/2022] Tao passed his Confirmation of Candidature milestone! Many thanks to the nice supervisory team and colleagues!