I am a PhD student in Computer Science at Vanderbilt University under the supervision of Dr. Tyler Derr and a member of the Network and Data Science (NDS) lab. I have completed my BS and MS in Computer Science from Huazhong University of Science and Technology in 2018 and 2021, respectively, where I received the university’s “Outstanding Graduate” award for both my BS degree and MS degree.

Research Interest

My research interests lie in the interface of Machine Learning and Graph Mining with specific focus on: Fairness-aware Graph Neural Networks, Explainable Graph Neural Networks, ML-based solutions for influence maximization problem. I am fascinated by the powerful representation ability of graphs. I am broadly interested in analyzing all kinds of graph data, ranging from social media networks, coauthorship relationships, biology graphs, EHR graphs in healthcare domain, and so on.



  • [DSE journal] Maximizing Influence over Streaming Graphs with Query Sequence
    • Yuying Zhao, Yunfei Hu, Pingpeng Yuan, Hai Jin
    • [Paper]
  • [CSCWD] Grace: An Efficient Parallel SPARQL Query System over Large-Scale RDF Data
    • Xiang Kang, Yuying Zhao, Pingpeng Yuan, Hai Jin
    • [Paper]

Preprints and Submissions

  • [under review] Inferring EHR Utilization Workflows through Audit Logs
  • [under review] Imbalanced Graph Classification via Graph-of-Graph Neural Networks

Symposiums and Workshops

  • Yuying Zhao. Improving Fairness via Fair Explanation. International Conference on Data Mining (SDM) Doctoral Forum, SIAM, Poster, 2022.