Huanmei Wu

Health Services Administration and Policy
Assistant Dean for Global Engagement
Office of the Dean
541 Ritter Annex


Dr. Huanmei Wu, with a BS in chemistry from Tsinghua University and a PhD in computer science from Northeastern University, currently serves as chair of the Department of Health Services Administration and Policy at Temple University's College of Public Health. She also holds the role of assistant dean for global engagement. Before joining Temple, she was chair of the Department of BioHealth Informatics at Indiana University School of Informatics and Computing–Indianapolis.

Dr. Wu is a multi-disciplinary researcher who applies data management and knowledge discovery in the fields of life science and public health. Her research spans a diverse range of topics, including advanced cancer radiotherapy, diabetes, cardiovascular disease, lupus, Alzheimer's disease, and other neurodegenerative conditions, with a strong emphasis on precision treatments and predictive modeling. She collaborates with academia, community health centers, research institutes, industrial partners, and local communities. Dr. Wu's research has secured funding from various agencies, such as NSF, NIH, USAID, PCORI, JDRF, RWJF, and more.

Dr. Wu's research interests include:

  • Managing, analyzing, and modeling integrated multi-source clinical data and social determinants of health for precision healthcare
  • Applying machine learning and artificial intelligence in healthcare
  • Enhancing public health and social well-being through real-world data and evidence
  • Predictive modeling and chronic disease management, encompassing but not limited to diabetes, hypertension, cardiovascular diseases, Alzheimer's disease, ALS, lupus, stroke, and other related conditions


  • PhD, Computer and Information Science, Northeastern University
  • BS, Chemistry, Tsinghua University

Courses Taught




HIM 5113

Database Administration for Health Informatics Professionals


Selected Publications

  • Liu, E., Wu, X., Wang, L., Huo, Y., Wu, H., Li, L., & Cheng, L. (2022). DSCN: Double-target selection guided by CRISPR screening and network. PLoS Comput Biol, 18(8), p. e1009421. United States. doi: 10.1371/journal.pcbi.1009421

  • Liu, J., Dong, C., Liu, Y., & Wu, H. (2021). CGPE: an integrated online server for Cancer Gene and Pathway Exploration. Bioinformatics, 37(15), pp. 2201-2202. England. doi: 10.1093/bioinformatics/btaa952

  • Yu, H., Lam, K., Green, M.D., Wu, H., Yang, L.i., Wang, W., Jin, J., Hu, C., Wang, Y., Jolly, S., & Kong, F. (2021). Significance of radiation esophagitis: Conditional survival assessment in patients with non-small cell lung cancer. Journal of the National Cancer Center, 1(2), pp. 31-38. doi: 10.1016/j.jncc.2021.02.003

  • Zhang, X., Li, C., Wang, X., & Wu, H. (2021). A novel fault diagnosis procedure based on improved symplectic geometry mode decomposition and optimized SVM. Measurement: Journal of the International Measurement Confederation, 173. doi: 10.1016/j.measurement.2020.108644

  • Purkayastha, S., Goyal, S., Oluwalade, B., Phillips, T., Wu, H., & Zou, X. (2021). Usability and security of different authentication methods for an electronic health records system. HEALTHINF 2021 - 14th International Conference on Health Informatics; Part of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2021, pp. 621-628.

  • Patel, J., Lai, P., Dormer, D., Gullapelli, R., Wu, H., & Jones, J.J. (2021). Comparison of Ease of Use and Comfort in Fitness Trackers for Participants Impaired by Parkinson's Disease: An exploratory study. AMIA Jt Summits Transl Sci Proc, 2021, pp. 505-514. United States. Retrieved from

  • Li, M., Prasad, N., Hall, D., & Wu, H. (2020). Analysis of SARS-CoV-2 sequences reveals transmission path and emergence of SD 614Gmutation. Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020, pp. 1995-1998. doi: 10.1109/BIBM49941.2020.9313091

  • Bone, R.N., Oyebamiji, O., Talware, S., Selvaraj, S., Krishnan, P., Syed, F., Wu, H., & Evans-Molina, C. (2020). A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes. Diabetes, 69(11), pp. 2364-2376. United States. doi: 10.2337/db20-0636

  • Wu, H. (2020). Community Partnerships for Enhanced Research Experience in Biomedical Informatics. Proceedings - Frontiers in Education Conference, FIE, 2020-October. doi: 10.1109/FIE44824.2020.9274116

  • Phillips, T., Yu, X., Haakenson, B., Goyal, S., Zou, X., Purkayastha, S., & Wu, H. (2020). AuthN-AuthZ: Integrated, User-Friendly and Privacy-Preserving Authentication and Authorization. Proceedings - 2020 2nd IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications, TPS-ISA 2020, pp. 189-198. doi: 10.1109/TPS-ISA50397.2020.00034

  • Liu, J., Dong, C., Jiang, G., Lu, X., Liu, Y., & Wu, H. (2020). Transcription factor expression as a predictor of colon cancer prognosis: a machine learning practice. BMC Med Genomics, 13(Suppl 9), p. 135. England. doi: 10.1186/s12920-020-00775-0

  • Dong, C., Liu, J., Chen, S.X., Dong, T., Jiang, G., Wang, Y., Wu, H., Reiter, J.L., & Liu, Y. (2020). Highly robust model of transcription regulator activity predicts breast cancer overall survival. BMC Med Genomics, 13(Suppl 5), p. 49. England. doi: 10.1186/s12920-020-0688-z

  • Li, L.i., Yu, P., Zhang, P., Wu, H., Chen, Q., Li, S., & Wang, Y. (2020). Upregulation of hsa_circ_0007874 suppresses the progression of ovarian cancer by regulating the miR-760/SOCS3 pathway. Cancer Med, 9(7), pp. 2491-2499. United States. doi: 10.1002/cam4.2866

  • Zhu, W., Han, Y., Wu, H., Liu, Y., Nan, X., & Zhou, Q. (2020). Predicting the results of molecular specific hybridization using boosted tree algorithm. Concurrency and Computation: Practice and Experience, 32(1). doi: 10.1002/cpe.4982

  • Yu, H., Lam, K., Wu, H., Green, M., Wang, W., Jin, J., Hu, C., Jolly, S., Wang, Y., & Kong, F.S. (2020). Weighted-Support Vector Machine Learning Classifier of Circulating Cytokine Biomarkers to Predict Radiation-Induced Lung Fibrosis in Non-Small-Cell Lung Cancer Patients. Front Oncol, 10, p. 601979. Switzerland. doi: 10.3389/fonc.2020.601979

  • Purkayastha, S., Goyal, S., Phillips, T., Wu, H., Haakenson, B., Zou, X., & Soc, I.C. (2020). Continuous Security through Integration Testing in an Electronic Health Records System. 2020 INTERNATIONAL CONFERENCE on SOFTWARE SECURITY and ASSURANCE (ICSSA 2020), pp. 26-31. doi: 10.1109/ICSSA51305.2020.00012

  • Jiang, H., Ramadan, A., Laurine, B., Szu-Wei, T.u., Liu, H., Rowan, C., Liu, X., Wu, H., Wan, J., & Paczesny, S. (2019). IL-33 Therapy Prevents Acute Lung Injury after Transplantation Via IL-9-Producing Type 2 Innate Lymphoid Cells Induction. BLOOD, 134. doi: 10.1182/blood-2019-123821

  • Zhu, W., Liu, X., Xu, M., & Wu, H. (2019). Predicting the results of RNA molecular specific hybridization using machine learning. IEEE/CAA Journal of Automatica Sinica, 6(6), pp. 1384-1396. doi: 10.1109/JAS.2019.1911756

  • Yu, H., Wu, H., Wang, W., Jolly, S., Jin, J., Hu, C., & Kong, F.S. (2019). Machine Learning to Build and Validate a Model for Radiation Pneumonitis Prediction in Patients with Non-Small Cell Lung Cancer. Clin Cancer Res, 25(14), pp. 4343-4350. United States. doi: 10.1158/1078-0432.CCR-18-1084

  • Wu, H., Kothiya, P., Khan, A., & Liu, J. (2019). Family-HealthVault: A group caring and phi sharing framework among family members. 2019 IEEE International Conference on Healthcare Informatics, ICHI 2019. doi: 10.1109/ICHI.2019.8904613

  • Kunjan, K., Wu, H., Toscos, T.R., & Doebbeling, B.N. (2019). Large-Scale Data Mining to Optimize Patient-Centered Scheduling at Health Centers. J Healthc Inform Res, 3(1), pp. 1-18. Switzerland. doi: 10.1007/s41666-018-0030-0

  • Hosseini, M., Faiola, A., Jones, J., Vreeman, D.J., Wu, H., & Dixon, B.E. (2019). Impact of document consolidation on healthcare providers' perceived workload and information reconciliation tasks: a mixed methods study. J Am Med Inform Assoc, 26(2), pp. 134-142. England. doi: 10.1093/jamia/ocy158

  • Kechavarzi, B.D., Wu, H., & Doman, T.N. (2019). Bottom-up, integrated -omics analysis identifies broadly dosage-sensitive genes in breast cancer samples from TCGA. PLoS One, 14(1), p. e0210910. United States. doi: 10.1371/journal.pone.0210910

  • Akino, Y., Wu, H., Oh, R., & Das, I.J. (2019). An effective method to reduce the interplay effects between respiratory motion and a uniform scanning proton beam irradiation for liver tumors: A case study. J Appl Clin Med Phys, 20(1), pp. 220-228. United States. doi: 10.1002/acm2.12508

  • Zhu, W., Wu, H., & Deng, M. (2019). LTL model checking based on binary classification of machine learning. IEEE Access, 7, pp. 135703-135719. doi: 10.1109/ACCESS.2019.2942762

  • Deng, M., Cao, H., Zhu, W., Wu, H., & Zhou, Y. (2019). Benchmark tests for the model-checking-based ids algorithms. IEEE Access, 7, pp. 135479-135498. doi: 10.1109/ACCESS.2019.2939011

  • Liu, X., Yue, Z., Cao, Y., Taylor, L., Zhang, Q., Choi, S.W., Hanash, S., Ito, S., Chen, J.Y., Wu, H., & Paczesny, S. (2019). Graft-Versus-Host Disease-Free Antitumoral Signature After Allogeneic Donor Lymphocyte Injection Identified by Proteomics and Systems Biology. JCO Precis Oncol, 3. United States. doi: 10.1200/po.18.00365

  • Lai, P.T.S., Wilson, J., Wu, H., Jones, J., & Dixon, B.E. (2019). Measuring and Visualizing Chlamydia and Gonorrhea Inequality: An Informatics Approach Using Geographical Information Systems. Online J Public Health Inform, 11(2), p. e8. Canada. doi: 10.5210/ojphi.v11i2.10155