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.
- Curriculum Vitae
- Email: yuying (dot) zhao (at) vanderbilt (dot) edu
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. 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.
- 01/2023: Our paper “Collaboration-Aware Graph Convolutional Network for Recommender Systems” is accepted by TheWebConf’23.
- 01/2023: Glad that I passed my preliminary exam.
- 12/2022: Glad to join Visa as a PhD research intern for Summer’23.
- 12/2022: Awarded AAAI-23 Student Scholarships and selected as volunteers.
- 11/2022: Our paper “Fairness and Explainability: Bridging the Gap Towards Fair Model Explanations” is accepted by AAAI’23.
- 08/2022: Our paper “Imbalanced Graph Classification via Graph-of-Graph Neural Networks” is accepted by CIKM’22.
- 07/2022: Our paper “Collaboration-Aware Graph Neural Networks for Recommendation Systems” is available now.
- 07/2022: Our paper “Inferring EHR Utilization Workflows through Audit Logs” is accpeted by AMIA’22.
- 06/2022: Awarded free registration for KDD’22.
- 05/2022: Our paper “Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage” is accepted by KDD’22.
- 04/2022: Poster presentation at SDM’22 Doctoral Forum.
- 04/2022: Awarded the SDM’22 travel award.
- 03/2022: Previous work on Influence Maximization has been promoted by CCF database committe.
- 02/2022: Give a guest lecture on Information Diffusion and Influence Maximization.
- [TheWebConf’23] Collaboration-Aware Graph Convolutional Networks for Recommendation Systems [Paper][Code]
- Yu Wang, Yuying Zhao, Yi Zhang, Tyler Derr
- [AAAI’23] Fairness and Explainability: Bridging the Gap Towards Fair Model Explanations [Paper][Code]
- Yuying Zhao, Yu Wang, Tyler Derr
- [CIKM] Imbalanced Graph Classification via Graph-of-Graph Neural Networks [Paper][Code]
- Yu Wang, Yuying Zhao, Neil Shah, Tyler Derr
- [KDD] Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage [Paper][Code]
- Yu Wang, Yuying Zhao, Yushun Dong, Huiyuan Chen, Jundong Li, Tyler Derr
- [AMIA] Inferring EHR Utilization Workflows through Audit Logs
- Yuying Zhao*, Xinmeng Zhang*, Chao Yan, Tyler Derr, You Chen
- [DSE journal] Maximizing Influence over Streaming Graphs with Query Sequence [Paper]
- Yuying Zhao, Yunfei Hu, Pingpeng Yuan, Hai Jin
- [CSCWD] Grace: An Efficient Parallel SPARQL Query System over Large-Scale RDF Data [Paper]
- Xiang Kang, Yuying Zhao, Pingpeng Yuan, Hai Jin
* denotes co-first author.
Preprints and Submissions
Symposiums and Workshops
- Yuying Zhao. Improving Fairness via Fair Explanation. International Conference on Data Mining (SDM) Doctoral Forum, SIAM, Poster, 2022.