I am a PhD Candidate 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 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

Research Interest

My research interests lie in Responsible and Trustworthy AI, focusing on learning beyond utility perspectives, including fairness, explainability, and diversity. My work spans various applications, such as recommender systems, graph neural networks, large language models, and traditional machine learning models.

News

• 10/2024: Our paper “Edge Classification on Graphs: New Directions in Topological Imbalance” has been accepted by WSDM.
• 09/2024: Our paper “FairNNV: The Neural Network Verification Tool For Certifying Fairness” has been accepted by ICAIF 24.
• 08/2024: Our survey “A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applications” has been accepted by TKDE.
• 07/2024: Our paper “Augmenting Textual Generation via Topology Aware Retrieval” is accepted by CIKM.
• 07/2024: Our paper “PSNE: Spectral Sparsification Algorithms for Scaling Network Embedding” is accepted by CIKM.
• 05/2024: Glad to share that I passed the qualifying exam.
• 04/2024: Our paper “Fairness and Diversity in Recommender Systems: A Survey” is accepted by ACM Transactions on Intelligent Systems and Technology (TIST).
• 02/2024: Glad to join Visa as a PhD research intern for Summer’24.
• 02/2024: Give a guest lecture on Fairness in Recommendation.
• 01/2024: Our paper “Can One Embedding Fit All? A Multi-Interest Learning Paradigm Towards Improving User Interest Diversity Fairness” is accepted by WWW’24.
• 01/2024: Our paper “A Topological Perspective on Demystifying GNN-Based Link Prediction Performance” is accepted by ICLR’24.
• 12/2023: Awarded AAAI-24 Student Scholarships and selected as volunteers.
• 12/2023: Our paper “Leveraging Opposite Gender Interaction Ratio as a Path towards Fairness in Online Dating Recommendations Based on User Sexual Orientation” is accepted by AAAI’24.
• 07/2023: The article “Progress and Promise: The Shifting Landscape of Gender in STEM” is available on KDD’23 blog.
• 07/2023: Our paper “Fairness and Diversity in Recommender Systems: A Survey” is available.
• 06/2023: Received Student Travel Award for the SIGKDD’23 to be held at Long Beach.
• 06/2023: Our paper “Fair Online Dating Recommendations for Sexually Fluid Users via Leveraging Opposite Gender Interaction Ratio” has been accepted by Workshop on Mining and Learning with Graphs (MLG) at KDD’23.
• 06/2023: Our paper “The Friendship Paradox: An Analysis on Signed Social Networks with Positive and Negative Links” has been accepted by Undergraduate Consortium at KDD’23.
• 05/2023: Received C.F. Chen Best Paper Runner-Up Award in Computer Science from Vanderbilt University.
• 04/2023: Our paper “ADEPT: Autoencoder with Differentially Expressed Genes and Imputation For A Robust Spatial Transcriptomics Clustering” is accepted by Journal iScience.
• 03/2023: Selected to participate in the SDM’23 Doctoral Forum and to receive the student travel award.
• 03/2023: Our paper “ADEPT: Autoencoder with Differentially Expressed Genes and Imputation For A Robust Spatial Transcriptomics Clustering” is accepted by RECOMB-SEQ 2023.
• 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 accepted 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.

Publications

2024

• [TKDE] A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applications [Paper]
  • Yuying Zhao*, Yi Zhang*, Zhaoqing Li, Xueqi Cheng, Yu Wang, Olivera Kotevska, Philip Yu, Tyler Derr
• [CIKM’24] Augmenting Textual Generation via Topology Aware Retrieval [Paper]
  • Yu Wang, Nedim Lipka, Ruiyi Zhang, Alexa Siu, Yuying Zhao, Bo Ni, Xin Wang, Ryan Rossi, Tyler Derr
• [CIKM’24] PSNE: Spectral Sparsification Algorithms for Scaling Network Embedding [Paper]
  • Longlong Lin, Yunfeng Yu, Zihao Wang, Zeli Wang, Yuying Zhao, Zhao Jin, Tao Jia
• [TIST] Fairness and Diversity in Recommender Systems: A Survey [Paper]
  • Yuying Zhao, Yu Wang, Yunchao Liu, Xueqi Cheng, Charu Aggarwal, Tyler Derr
• [TheWebConf’24] Can One Embedding Fit All? A Multi-Interest Learning Paradigm Towards Improving User Interest Diversity Fairness [Paper][Code]
  • Yuying Zhao, Minghua Xu, Huiyuan Chen, Yuzhong Chen, Yiwei Cai, Rashidul Islam, Yu Wang, Tyler Derr
• [AAAI’24] Leveraging Opposite Gender Interaction Ratio as a Path towards Fairness in Online Dating Recommendations Based on User Sexual Orientation [Paper][Code]
  • Yuying Zhao, Yu Wang, Yi Zhang, Pamela Wisniewski, Charu Aggarwal, Tyler Derr
• [ICLR’24] A Topological Perspective on Demystifying GNN-Based Link Prediction Performance [Paper][Code]
  • Yu Wang, Tong Zhao, Yuying Zhao, Yunchao Liu, Xueqi Cheng, Neil Shah, Tyler Derr

2023

• [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

2022

• [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

Before 2022

• [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.

Symposiums and Workshops

• Yuying Zhao. Learning Beyond Utility: Fairness, Explainability, Diversity. International Conference on Data Mining (SDM) Doctoral Forum, SIAM, Poster, 2023.
• Yuying Zhao. Improving Fairness via Fair Explanation. International Conference on Data Mining (SDM) Doctoral Forum, SIAM, Poster, 2022.