Yinghao Fu

Yinghao Fu

Welcome!

I am Yinghao FU, currently a second-year Ph.D. student in Biostatistics at the City University of Hong Kong (CityU), where I am mentored by Professor Yi Yang. Prior to this, I obtained my Master’s degree from The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), where I am advised by Professor Tianwei Yu and Shuang Li.

My research focuses on developing data-driven and theory-driven methods to address challenges in genomics data analysis, with applications in healthcare.

If you are interested in my work, please feel free to drop me an email.

🔥 News

  • 2026.05: One paper was accepted at ICML 2026.
  • 2025.09: One paper was awarded Best Paper at the NeurIPS 2025 Workshop on GenAI for Health: Potential, Trust, and Policy Compliance.
  • 2025.06: Three papers accepted to ICML 2025 Workshops:
  • 2025.03: One paper accepted in Frontiers in Genetics.
  • 2024.07: Gave an invited talk at the EcoStat Conference, Beijing.
  • 2024.05: One paper accepted at ICML 2024.
  • 2024.04: One paper accepted in Genome Research.
  • 2024.01: Gave a talk at PMOSHK, Hong Kong.
  • 2024.01: One paper accepted at ICLR 2024.

📝 Publications

(* indicates equal contribution)

Journal

  1. Fu, Y., & Yang, Y. (2026+).
    Knockoff-augmented neural networks for identifying risk variants in family-based association studies.

  2. Fu, Y., Tian, L., & Zhang, W. (2025).
    STsisal: a reference-free deconvolution pipeline for spatial transcriptomics data.
    Frontiers in Genetics.

  3. Cai, Q.*, Fu, Y.*, Lyu, C.*, Wang, Z., Rao, S., Alvarez, J. A., Bai, Y., Kang, J., & Yu, T. (2024).
    A new framework for exploratory network mediator analysis in omics data.
    Genome Research.

Conference

  1. Yan, Y., Fu, Y., Ren, W., & Li, S.
    Beyond Accuracy: Latent Perturbations for Cognitive-Aware Diagnosis.

    International Conference on Machine Learning (ICML 2026).

  2. Cao, C.*, Fu, Y.*, Xv, S., Zhang, R., & Li, S. (2024).
    Enhancing Human-AI Collaboration Through Logic-Guided Reasoning.
    International Conference on Learning Representations (ICLR 2024).

  3. Yang, Y., Yang, C., Li, B., Fu, Y., & Li, S. (2024).
    Neuro-Symbolic Temporal Point Processes.
    International Conference on Machine Learning (ICML 2024).

  4. Xia, W., Fu, Y., Shi, J., Wu, H., & Wang, J. (2021).
    The Team Winning Analysis Model Based on Network and Entropy Weight.
    40th Chinese Control Conference (CCC 2021).

Workshop

  1. Fu, Y.*, Yang, C.*, Chen, X., Yan, Y., & Li, S.
    Who Should Be Consulted? Targeted Expert Selection for Rare Disease Diagnosis.
    ICML 2025 Workshop on Collaborative and Federated Agentic Workflows.
    (Oral)

  2. Yan, Y., Fu, Y., Ren, W., & Li, S.
    Unanchoring the Mind: DAE-Guided Counterfactual Reasoning for Rare Disease Diagnosis.
    NeurIPS 2025 Workshop on GenAI for Health: Potential, Trust, and Policy Compliance
    (Oral, Best Paper Award);
    ICML 2025 Workshop on Models of Human Feedback for AI Alignment.

  3. Cao, C., Fu, Y., Yang, C., & Li, S.
    Discovering Logic-Informed Intrinsic Rewards to Explain Human Policies.
    ICML 2025 Workshop on Programmatic Representations for Agent Learning.

Patent

  1. Li, S., Fu, Y., Yang, C., Yang, Y., Feng, M., Xia, P., Chen, L., & Yu, T. (2024).
    An AI-Assisted Multidisciplinary Consultation Decision-Making Method for Complex and Rare Diseases. Publication No. CN118507022A.

📖 Educations

  • Ph.D. in Biostatistics (2024-Present)
    City University of Hong Kong
    Advisor: Yi Yang

  • M.Sc. in Bioinformatics (2022-2024)
    The Chinese University of Hong Kong, Shenzhen
    Advisors: Tianwei Yu and Shuang Li

  • B.Sc. in Statistics (2018-2022)
    East China University of Technology
    Advisor: Weiwei Zhang

💬 Invited Talks

💻 Services

  • Conference Reviewer: NeurIPS, ICML, ICLR, AISTATS, AAMAS
  • Workshop Reviewer: ICML 2025 Workshop MAS

📝 Teaching

  • BIOS 5802: Advanced Methods in Biostatistics (Spring 2025)