Xiyang Hu

Carnegie Mellon University

Xiyang Hu (pronunciation: “SHEE-yung HOO”, 胡曦阳 in Chinese) is currently a Research Scientist at Tiktok. He got his Ph.D. in Information Systems at Carnegie Mellon University, M.Sc. in Statistical Science from Duke University, and B.Arch. in Architecture with a minor in Computer Science from Tsinghua University.

We are hiring at Tiktok!

I am committed to promoting Diversity, Equity, and Inclusion in my work, teaching, and collaborations.

Check out my Google Scholar .

Research Interests

  • Foundation Models
  • Human-Centered AI
  • Data-Centric ML
  • Out of Distribution Detection
  • Natural Language Processing
  • Open-Source

Professional Services

Area Chair: ICML

Program Committee and/or Reviewer: ACL(2024), MS, TKDE, FAccT(2023), EACL(2023), KDD (2023), WITS (2022), NeurIPS (2022), ANDEA (2022), CSWIM (2022), CIST (2022), ICIS (2022), KDD (2022), AAAI (2021), CIST (2021), INFORMS (2021)

Honors & Awards

news

Jan 18, 2022 Excited to release the first comprehensive open-sourced graph outlier detection libraryPyGOD. :satisfied:

selected publications

  1. NeurIPS
    ADGym: Design Choices for Deep Anomaly Detection
    Jiang, Minqi, Hou, Chaochuan, Zheng, Ao, Han, Songqiao, Huang, Hailiang, Wen, Qingsong, Hu, Xiyang, and Zhao, Yue
    Advances in Neural Information Processing Systems 2023
  2. ACL
    Language Agnostic Multilingual Information Retrieval with Contrastive Learning
    Hu, Xiyang, Chen, Xinchi, Qi, Peng, Kong, Deguang, Liu, Kunlun, Wang, William Yang, and Huang, Zhiheng
    Annual Meeting of the Association for Computational Linguistics - Findings of ACL 2023
  3. preprint
    Inclusive Decision Making via Contrastive Learning and Domain Adaptation
    Hu, Xiyang, Huang, Yan, Li, Beibei, and Lu, Tian
    MIS Quarterly (Under Major Revision) 2023
  4. preprint
    Weakly Supervised Anomaly Detection: A Survey
    Jiang, Minqi, Hou, Chaochuan, Zheng, Ao, Hu, Xiyang, Han, Songqiao, Huang, Hailiang, He, Xiangnan, Yu, Philip S, and Zhao, Yue
    arXiv preprint arXiv:2302.04549 2023
  5. preprint
    Human-Algorithmic Bias: Source, Evolution, and Impact
    Hu, Xiyang, Huang, Yan, Li, Beibei, and Lu, Tian
    Management Science (Under Major Revision) 2022
  6. NeurIPS
    ADBench: Anomaly Detection Benchmark
    Hu, Xiyang, Han, Songqiao, Huang, Hailiang, Jiang, Mingqi, and Zhao, Yue
    Advances in Neural Information Processing Systems 2022
  7. NeurIPS
    Benchmarking Node Outlier Detection on Graphs
    Liu, Kay, Dou, Yingtong, Zhao, Yue, Ding, Xueying, Hu, Xiyang, Zhang, Ruitong, Ding, Kaize, Chen, Canyu, Peng, Hao, Shu, Kai, and others,
    Advances in Neural Information Processing Systems 2022
  8. ICIS
    Credit Risk Modeling without Sensitive Features: An Adversarial Deep Learning Model for Fairness and Profit
    Hu, Xiyang, Huang, Yan, Li, Beibei, and Lu, Tian
    International Conference on Information Systems 2022
  9. preprint
    PyGOD: A Python Library for Graph Outlier Detection
    Liu, Kay, Dou, Yingtong, Ding, Xueying, Hu, Xiyang, Zhang, Ruitong, Peng, Hao, Sun, Lichao, and Yu, Philip
    arXiv preprint arXiv:2204.12095 2022
  10. TKDE
    ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions
    Li, Zheng, Zhao, Yue, Hu, Xiyang, Botta, Nicola, Ionescu, Cezar, and Chen, George H
    IEEE Transactions on Knowledge and Data Engineering 2022
  11. ICIS
    Uncovering the Source of Evaluation Bias in Micro-Lending
    Hu, Xiyang, Huang, Yan, Li, Beibei, and Lu, Tian
    International Conference on Information Systems 2021
  12. MLSys
    SUOD: Accelerating Large-scale Unsupervised Heterogeneous Outlier Detection
    Hu, Xiyang, Zhao, Yue, Cheng, Cheng, Wang, Cong, Wan, Changlin, Wang, Wen, Yang, Jianing, Bai, Haoping, LI, Zheng, Xiao, Cao, Wang, Yunlong, Qiao, Zhi, Sun, Jimeng, and Akoglu, Leman
    Conference on Machine Learning and Systems 2021
  13. KDD
    Uncovering the Source of Machine Bias [CIST 2021 Best Student Paper Nomination:trophy:]
    Hu, Xiyang, Huang, Yan, Li, Beibei, and Lu, Tian
    27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Machine Learning for Consumers and Markets Workshop 2021
  14. ICDM
    COPOD: Copula-Based Outlier Detection
    LI, Zheng, Zhao, Yue, Botta, Nicola, Ionescu, Cezar, and Hu, Xiyang
    IEEE International Conference on Data Mining 2020
  15. NeurIPS
    Optimal Sparse Decision Trees [NeurIPS 2019 Spotlight:trophy: (Top 3%)]
    Hu, Xiyang, Rudin, Cynthia, and Seltzer, Margo
    Advances in Neural Information Processing Systems 2019