About Me

Dr. Yongqi Zhang is now a tenue-track assistant professor in DSA Thrust at HKUST(GZ). Prior to this, he worked as a research scientist at the AI listed company 4Paradigm Inc. and collaborated closely with Prof. Quanming Yao at Tsinghua University. In terms of education, Dr. Zhang completed his doctoral degree in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology (HKUST) in 2020, advised by Prof. Lei Chen. Before pursuing his Ph.D., he obtained a bachelor’s degree from Shanghai Jiao Tong University (SJTU) in 2015. With this background, Dr. Zhang possesses extensive academic and industry experience, as well as strong collaborations with partners.

Email: yongqizhang at hkust-gz dot edu dot cn

Research Topics

My research primarily revolves around learning from relational graph data, with a focus on modeling graph structures, object relationships, utilizing various resources, and interpreting the inference processes. In the near future, I anticipate generative models, such as large language models, to become a key aspect of my research. Additionally, I am intrigued by the application of graph learning techniques in interdisciplinary research, particularly within the biomedical field. A visual representation of my research ideas is depicted in the following figure.

Keywords: graph learning, graph neural network, automated machine learning, generative AI, large language model, graph for science.

Representative publications recently:
[1] Yongqi Zhang, Quanming Yao*, Ling Yue, Xian Wu, Ziheng Zhang, Zhenxi Lin and Yefeng Zheng. (EmerGNN) Emerging Drug Interaction Prediction Enabled by Flow-based Graph Neural Network with Biomedical Network. Nature Computational Science. 2023.
[2] Yongqi Zhang, Quanming Yao* and James T. Kwok. (AutoBLM) Bilinear Scoring Function Search for Knowledge Graph Learning. IEEE TPAMI. 2023.
[3] Yongqi Zhang and Quanming Yao*. (RED-GNN) Knowledge Graph Reasoning with Relational Directed Graph. The WebConf. 2022.