Yan Hou

Tenured Associate Professor, Researcher
houyan@bjmu.edu.cn
38 College Road, Beijing, China, 100191
Peking University

Personal profile

Dr. Yan Hou is a Tenured Associate Professor in the Department of Biostatistics at Peking University, and is also appointed at Peking University Cancer Hospital. She currently serves as Director of the Committee on Innovation, Translation and Evaluation of Drug Regulatory Science at the China Food and Drug Enterprise Quality and Safety Promotion Association; Vice Director of the Committee on Biostatistical Education at the Chinese Health Information and Big Data Association; Standing Committee Member and Vice Director of the Youth Committee of the Biostatistics Professional Committee at the Chinese Preventive Medicine Association; Standing Committee Member of the Pharmaceutical Statistics Committee at the China Medical Education Association; and Standing Committee Member of the Chinese Medical and Health Systems Engineering Professional Committee, among other professional appointments. She has conducted systematic research on statistical methodology in clinical studies. Over the past five years, she has led multiple National Key R&D Programs, National Science and Technology Major Projects, and General Programs of the National Natural Science Foundation of China. She also leads the Peking University Medicine–LinkDoc Joint Laboratory and the Peking University Medicine–CNBG Joint Laboratory, and has led multiple regulatory science research projects commissioned by the National Medical Products Administration (NMPA) on ICH E-series guidelines. She has led or participated in the development of multiple industry guidelines, group standards, and expert consensuses; edited and co-edited multiple national planning textbooks; and served as the first translator for multiple works. She has been granted more than ten national invention patents, and has published approximately 100 academic papers as corresponding or first author in high-level journals in relevant research fields.

Main research directions

Biostatistics (Regulatory Science): Theoretical Methods and Applications

Representative scientific research projects

1. National Science and Technology Major Project for Prevention and Control of Emerging and Major Infectious Diseases (2025ZD01906004), Study on Biomarker Screening and Mechanism of Hepatitis B Cirrhosis Reversal Driven by Multi-modal Time-series Data (2026/01-2028/12), hosted.

2. General Project of the National Natural Science Foundation of China (82674775), Study on Drug Repositioning Based on Ontology Knowledge Transfer-guided Bayesian Federated Learning (2027/01-2030/12), hosted.

3. General Project of the National Natural Science Foundation of China (82373682), Study on Predictive Modeling and Application of Targeted Drug Sensitivity Based on Multi-omics Adversarial Auto-regressive Neural Networks (2024/01-2027/12), hosted.

4. Commissioned Project of LinkDoc Technology (Beijing) Co., Ltd., Peking University Medicine–LinkDoc Joint Laboratory for Real-World Evidence Translation and Regulatory Science (2025/10-2028/09), hosted.

5. Commissioned Project of China National Biotec Group Co., Ltd., Peking University Medicine–CNBG Joint Laboratory for Clinical and Regulatory Science (2021/09-2024/08), hosted.

6. National Key R&D Program of the Ministry of Science and Technology (2021YFF0901401), Study on Regulatory Data Modeling and Analysis Technology Based on Medical Ontology (2021/12-2024/11), hosted.

7. General Project of the National Natural Science Foundation of China (82173615), Study on Targeted Drug Screening and Molecular Action Prediction Methods Based on Auto-encoder and Ensemble Learning Algorithms (2022/01-2025/12), hosted.

10 representative papers

1. He J, Li Y, Hou Y*. A group structure guided ultra-high dimensional feature screening for survival outcome. Statistics in Medicine. 2026; In press.

2. Song J, Rong Z*, Hou Y*. Variational biomarker pooling with calibration for time-to-event outcomes across multiple clinical studies. BMC Medical Research Methodology. 2026; 26(1): 97.

3. Yu Y, Long M, Song J, Cao K, Luo M, Liu W, Rong Z*, Hou Y*. GAMMI: Graph-Guided Contrastive and Adversarial Integration of Single-cell and Spatial Multi-omics Data. Briefings in Bioinformatics. 2026; 27(3): bbag218.

4. Huang J, Jia F, Li J, Xie W, Rong Z, Mi L, Song Y, Hou Y*. Dynamic Information Borrowing From External Data in Clinical Trials: The Elastic Commensurate Prior Approach. Statistics in Medicine. 2025; 44(13-14): e70129.

5. Rong Z, Song J, Sun F, Zhang C, Mi L, Song Y, Hou Y*. Bayesian biomarker effect estimate for combining data from multiple biomarker studies. Journal of applied statistics. 2025; 53(4): 614-632.

6. Rong Z, Song J, Yu Y, Mi L, Qiu M, Song Y, Hou Y*. Single-cell mosaic integration and cell state transfer with auto-scaling self-attention mechanism. Briefings in bioinformatics. 2024; 25(6): bbae540.

7. Long M, Song J, Rong Z, Mi L, Song Y, Hou Y*. Adaptively leverage multiple real-world data sources for treatment effect estimation based on similarity. Journal of Biopharmaceutical Statistics. 2024; 34(6): 853-863.

8. Cao L, Wang J, Zhang Y, Rong Z, Wang M , Wang L, Ji J, Qian Y , Zhang L, Wu H, Song J, Liu Z, Wang W, Li S, Wang P, Xu Z, Zhang J, Zhao L, Wang H, Sun M, Huang X, Yin R, Lu Y, Liu Z, Deng K , Wang G, Qiu M*, Li K*, Wang J*, Hou Y*. E2EFP-MIL: End-to-end and high-generalizability weakly supervised deep convolutional network for lung cancer classification from whole slide image. Medical Image Analysis. 2023; 88: 102837.

9. He J, Song J, Zhou X*, Hou Y*. A screening method for ultra-high dimensional features with overlapped partition structures. Statistical Methods in Medical Research. 2023; 32(1): 22-40.

10. Rong Z, Liu Z, Song J, Cao L, Yu Y, Qiu M*, Hou Y*. MCluster-VAEs: an end-to-end variational deep learning-based clustering method for subtype discovery using multi-omics data. Computers in Biology and Medicine. 2022; 150: 106085.