Yinghao Fu

Yinghao Fu

Welcome!

I am Yinghao FU, currently a third-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 was advised by Professor Tianwei Yu and Professor Shuang Li.

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

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

🔥 News

  • 2026.09: One paper was accepted for publication in Genome Biology.
  • 2026.06: One paper was accepted to an ICML 2026 Workshop:
    • 🗣️ Oral presentation at the FAGEN Workshop
  • 2026.05: One paper was accepted to ICML 2026.
  • 2025.09: One paper received the Best Paper Award at the NeurIPS 2025 Workshop on GenAI for Health: Potential, Trust, and Policy Compliance.
  • 2025.06: Three papers were accepted to ICML 2025 Workshops:
  • 2025.03: One paper was accepted for publication in Frontiers in Genetics.
  • 2024.07: Gave an invited talk at the EcoStat Conference in Beijing.
  • 2024.05: One paper was accepted to ICML 2024.
  • 2024.04: One paper was accepted for publication in Genome Research.
  • 2024.01: Gave a talk at PMOSHK in Hong Kong.
  • 2024.01: One paper was accepted to ICLR 2024.

📝 Publications

(* indicates equal contribution)

Journal

  1. Fu, Y., & Yang, Y. (2026+).
    Shared-distinct representation learning decouples genetic and clinical risk signals for disease risk prediction.

  2. Fu, Y., & Yang, Y. (2026).
    KNOT: a knockoff-augmented neural network for identifying risk variants and epistatic interactions in family-based association studies.
    Genome Biology.

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

  4. 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. (2026).
    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. Yan, Y., Fu, Y., Gao, H., Zhang, T., Liu, A., & Li, S. (2025).
    When Agreement Becomes Unsafe: Loss-Aware Energy Control for Diagnostic Deliberation.
    ICML 2025 Workshop on Failure Modes of Agentic AI.
    (Oral Presentation)

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

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

  4. Cao, C., Fu, Y., Yang, C., & Li, S. (2025).
    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.

📖 Education

  • 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

💬 Invited Talks

💻 Service

  • Journal Reviewer: Transactions on Machine Learning Research (TMLR)
  • Conference Reviewer: NeurIPS, ICML, ICLR, AAAI, AISTATS, and AAMAS

📝 Teaching

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