About
Qian Tao, Professor, PhD/MA Supervisor, and Postdoctoral Research Supervisor at the School of Software Engineering, South China University of Technology (SCUT). He graduated from Sun Yat-sen University with a major in Computer Applications in June 2011. He pursued postdoctoral research at the Key Laboratory of High-Performance Data Mining, Chinese Academy of Sciences from December 2012 to August 2015, and served as a Visiting Scholar at the University of Rhode Island (USA) from October 2017 to November 2018. He is the recipient of the honorary title of Outstanding (Doctoral) Graduate of Guangdong Province. Currently, he holds the positions of Vice Dean of the School of Software Engineering at SCUT and Director of the Future City (Smart City) Software Laboratory. His research interests include artificial intelligence, graph deep learning, and smart city basic software. He has conducted academic visits and exchanges at universities such as the University of Rhode Island (USA) and the University of Cambridge (UK). He has published over 60 scientific research papers, authored 2 monographs, and applied for nearly 50 patents/software copyrights. He has presided over nearly 20 national and provincial-level scientific research projects. Research projects presided over in the past 5 years: 1 Special Project of NSFC-Guangdong Joint Fund for Supercomputing Science Application Research, 1 Sub-project (Task) of the National 863 Program, 1 China Postdoctoral Science Foundation Project, 2 Guangdong Provincial Natural Science Foundation Projects, 2 Guangdong Provincial Science and Technology Plan Projects, 1 Guangzhou Municipal Science and Technology Plan Project, 2 Guangdong Provincial Department of Education Projects, 1 Special Fund Project for Basic Scientific Research Business Fees of Central Universities, and 1 Google Curriculum Reform Project. He has implemented 7 horizontal projects as project manager and undertaken 1 Key Project of Guangdong Provincial Natural Science Foundation as partner principal investigator.
Education
October 2017 – November 2018, Visiting Scholar, University of Rhode Island, USA December 2012 – August 2015, Postdoctoral Researcher in Computer Science and Technology, Key Laboratory of High-Performance Data Mining, Chinese Academy of Sciences September 2008 – June 2011, PhD in Computer Application, Sun Yat-sen University September 2004 – December 2006, Master in Software Engineering, Huazhong University of Science and Technology
Research
Artificial Intelligence (Multimodal Large Models, Graph Deep Learning and Theory, Generative Adversarial Networks), Smart City (Smart City Basic Software, Disaster Early Warning and Targeted Software, Emergency Management Software, Smart Engine and Platform Software), Natural Language Processing (Dialogue Robots, Text Generation, Text Classification, Sentiment Analysis)
Thesis
- Tao, Qian;Liu, Chenghao;Xia, Yuhan;Xu, Yong;Li, Lusi,Adaptive multi-graph contrastive learning for bundle recommendation,Neural Networks,2025
- Tao, Qian;Cai, Rongshen;Lin, Zicheng;Tang, Yufei,Automatic Design of Deep Graph Neural Networks With Decoupled Mode,IEEE Transactions on Neural Networks and Learning Systems,2025
- Tao, Qian; Li, Ziyan; Han, Bocheng; Li, Lusi,Structure-Aware Dual Adversarial Autoencoder for Unsupervised Bilingual Lexicon Induction,IEEE Transactions on Audio, Speech and Language Processing,2025
- Liao, Jianpeng; Zhang, Enze; Li, Lusi,A Novel Hypergraph Neural Network Combining Multi-View Learning with Density Awareness,Pattern Recognition,2025
- Han, Jiadi;Tang, Yufei;Tao, Qian;Xia, Yuhan;Zhang, Liming,Dual Homogeneity Hypergraph Motifs with Cross-view Contrastive Learning for Multiple Social Recommendations,ACM Transactions on Knowledge Discovery from Data,2024
- Tao, Qian;Liao, Jianpeng;Zhang, Enze;Li, Lusi,A Dual Robust Graph Neural Network Against Graph Adversarial Attacks,Neural Networks,2024
- Tao, Qian;Xiong, Zhihao;Han, Bocheng;Fan, Xiaoyang;Li, Lusi,A Novel Unsupervised Approach for Cross-Lingual Word Alignment in Low Isomorphic Embedding Spaces,IEEE/ACM Transactions on Audio Speech and Language Processing,2023
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