🍭 Recent Publications (2021-)

See my Google Scholar, DBLP, ORCID, and ResearchGate for the full publication list. ^†Equal contribution; ^♠Corresponding author

Preprints & Working Papers

[w23g] Fast Unsupervised Deep Outlier Model Selection with Hypernetworks, with Xueying Ding, Leman Akoglu. Preprint.

[w23a] Weakly Supervised Anomaly Detection: A Survey, with Minqi Jiang, Chaochuan Hou, Ao Zheng, Xiyang Hu, Songqiao Han, Hailiang Huang, Xiangnan He, Philip S. Yu. Preprint.

[w22e] Hyperparameter Optimization for Unsupervised Outlier Detection, with Leman Akoglu. Preprint.

Conference Papers

• ADGym: Design Choices for Deep Anomaly Detection.
  Minqi Jiang^†, Chaochuan Hou^†, Ao Zheng^†, Songqiao Han, Hailiang Huang^♠, Qingsong Wen, Xiyang Hu^♠, Yue Zhao^♠.
  NeurIPS, 2023. .
• DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection.
  Jaemin Yoo, Yue Zhao, Lingxiao Zhao, Leman Akoglu.
  ECML/PKDD, 2023.
• Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks.
  Peng Xu^†, Lin Zhang^†, Xuanzhou Liu, Jiaqi Sun, Yue Zhao, Haiqin Yang, Bei Yu.
  ICML, 2023.
• TOD: GPU-accelerated Outlier Detection via Tensor Operations.
  Yue Zhao, George H. Chen, Zhihao Jia.
  VLDB, 2023.
• ADMoE: Anomaly Detection with Mixture-of-Experts from Noisy Labels.
  Yue Zhao, Guoqing Zheng, Subhabrata Mukherjee, Robert McCann, Ahmed Awadallah.
  AAAI, 2023.
• ADBench: Anomaly Detection Benchmark.
  Songqiao Han^†, Xiyang Hu^†, Hailiang Huang^†, Minqi Jiang^†, Yue Zhao^†♠.
  NeurIPS, 2022.
• BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs.
  Kay Liu^†, Yingtong Dou^†, Yue Zhao^†, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu.
  NeurIPS, 2022.
• ELECT: Toward Unsupervised Outlier Model Selection.
  Yue Zhao, Sean Zhang, Leman Akoglu.
  ICDM, 2022.
• Automatic Unsupervised Outlier Model Selection.
  Yue Zhao, Ryan Rossi, Leman Akoglu.
  NeurIPS, 2021.
• Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development.
  Kexin Huang^†, Tianfan Fu^†, Wenhao Gao^†, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik.
  NeurIPS, 2021.
• Revisiting Time Series Outlier Detection: Definitions and Benchmarks.
  Kwei-Herng Lai^†, Daochen Zha^†, Junjie Xu, Yue Zhao, Guanchu Wang, Xia Hu.
  NeurIPS, 2021.
• SUOD: Accelerating Large-scale Unsupervised Heterogeneous Outlier Detection.
  Yue Zhao^†, Xiyang Hu^†, Cheng Cheng, Cong Wang, Changlin Wan, Wen Wang, Jianing Yang, Haoping Bai, Zheng Li, Cao Xiao, Yunlong Wang, Zhi Qiao, Jimeng Sun, Leman Akoglu.
  MLSys, 2021.

Journal Papers

• Diffusion Models: A Comprehensive Survey of Methods and Applications.
  Ling Yang^†, Zhilong Zhang^†, Yang Song, Shenda Hong, Runsheng Xu, Yue Zhao, Wentao Zhang, Bin Cui, Ming-Hsuan.
  ACM Computing Surveys, 2023.
• The Need for Unsupervised Outlier Model Selection: A Review and Evaluation of Internal Evaluation Strategies.
  Martin Q. Ma^†, Yue Zhao^†, Xiaorong Zhang, Leman Akoglu.
  ACM SIGKDD Explorations Newsletter, 2023.
• Artificial Intelligence Foundation for Therapeutic Science.
  Kexin Huang^†, Tianfan Fu^†, Wenhao Gao^†, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik.
  Nature Chemical Biology, 2022.
• ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions.
  Zheng Li^†, Yue Zhao^†♠, Xiyang Hu, Nicola Botta, Cezar Ionescu, George H. Chen.
  TKDE, 2022.
• PyOD: A Python Toolbox for Scalable Outlier Detection.
  Yue Zhao, Zain Nasrullah, Zheng Li.
  JMLR, 2019.

💯 Teaching

USC (as instructor):

• Machine Learning (Spring 2024; to be finalized)

CMU (as teaching assistant):

• Intro to Artificial Intelligence (Spring 2020-Spring 2022)
• Digital Transformation (Spring 2022)
• Statistics for IT Managers (Fall 2021)

University of Toronto (as teaching assistant):

• Embedded Systems (Fall 2015)

🏅 Awards and Grants

- Meta AI4AI Research Award (co-PI), 2022

- Norton Labs Graduate Fellowship, 2022

- CMU Presidential Fellowship, 2019

- Mantei/Mae Academic Achievement Award, 2011-2015