My publication history can be viewed through my Google Scholar page. Alternatively, you can find below a more structured presentation.
Causal inference under network interference with noise. Li, W., Sussman, D. L., and Kolaczyk, E. D.
A text message intervention to minimize the time burden of cancer care. (2025) Bange, E.M., et al. NEJM Catalyst Innovations in Care Delivery, 6(3), CAT-24.
Deep learning-based approaches for multi-omics data integration and analysis. (2024) Ballard, J., Wang, Z., Li, W., Shen, L., and Long, Q. BioData Mining, 17, 38.
Graph-guided Bayesian factor model for integrative analysis of multi-modal data with noisy network information. (2024) Li, W., Zhang, Q., Qu, K., and Long, Q. Statistics in Biosciences, 1-17.
Circulating KRAS G12D but not G12V is associated with survival in metastatic pancreatic ductal adenocarcinoma. (2024) Till, J. E., et al. Nature Communications, 15(1), 5763.
The CNS relapse in T-cell lymphoma index predicts CNS relapse in patients with T-and NK-cell lymphomas. (2024) Bhansali, R. S., et al. Blood Advances, 8(13), 3507-3518.
Knowledge-guided learning methods for integrative analysis of multi-omics data. (2024) Li, W., Ballard, J., Zhao, Y., and Long, Q. Computational and Structural Biotechnology Journal, 23, 1945-1950.
Accounting for network noise in graph-guided Bayesian modeling of structured high-dimensional data. (2024) Li, W., Chang, C., Kundu, S., and Long, Q. Biometrics, 80(1), ujae012.
Multilevel stochastic optimization for imputation in massive medical data records. (2024) Li, W., Wang, W., Sun, Y., Milanovic, S., Kon M., and Castrillon-Candas, J.E. IEEE Transactions on Big Data, 10(2), 122-131.
Microbial gene expression analysis of healthy and cancerous esophagus uncovers bacterial biomarkers of clinical outcomes. (2023) Schäffer, D. E., Li, W., Elbasir, A., Altieri, D. C., Long, Q., and Auslander, N. ISME Communications, 3, 128.
Estimation of the branching factor in noisy networks. (2023) Li, W., Sussman, D. L., and Kolaczyk, E. D. IEEE Transactions on Network Science and Engineering, 10(1), 565-577.
Estimation of local time-varying reproduction numbers in noisy surveillance data. (2022) Li, W., Bulekova, K., Gregor, B., White, L. F., and Kolaczyk, E. D. Philosophical Transactions of the Royal Society A, 380(2233), 20210303.
Accuracy of a text intervention to minimize the burden of cancer care among patients treated with immune checkpoint inhibitors. (2022) Bange, E. M., Coughlin, K., Li, W., Moriarty, E., Brown, T. J., Shulman, L. N., and Mamtani, R. JAMA Network Open, 5(8), e2228452-e2228452.
Projecting quarantine utilization during a pandemic. (2022) Li, W., Kolaczyk, E. D., and White, L. F. American Journal of Public Health, 112(2), 277-283.
Assessment of a COVID-19 control plan on an urban university campus during a second wave of the pandemic. (2021) Hamer, D. H., White, L. F., Jenkins, H. E., Gill, C. J., Landsberg, H. E., Klapperich, C., Bulekova K., Platt J., Decarie L., Gilmore W., Pilkington M., MacDowell T. L., Faria M. A., Densmore D., Landaverde L., Li, W., Rose T., Burgay S. P., Miller C., Doucette-Stamm L., Lockard K., Elmore K., Schroeder T., Zaia A. M., Kolaczyk E. D., Waters G., and Brown, R. A. JAMA Network Open, 4(6), e2116425-e2116425.
Text intervention to minimize time burden of cancer care (TIME). (2023) Bange, E.M., et al. JCO Oncology Practice, 19 (supplement 11), 301-301.
Are we ready to mitigate time toxicity of cancer care? Oncologists' perceptions on digital interventions to fast-track cancer care. (2023) Bange, E.M., et al. Journal of Clinical Oncology, 41 (supplement 16), 1537-1537.
CNS relapse in T-cell lymphoma index: a risk score to predict central nervous system relapse in patients with T-cell lymphomas. (2022) Bhansali, R. S., et al. Blood, 140 (supplement 1), 1481-1484.
Characterizing mature T-cell lymphoma patients' outcomes by race. (2022) Cao, M., et al. Blood, 140 (supplement 1), 12013-12015.
Saving TIME: accuracy of a text intervention to minimize the time burden of cancer care. (2022) Bange, E.M., et al. Journal of Clinical Oncology, 40 (supplement 16), 6527-6527.
Network recovery from unlabeled noisy samples. (2021) Josephs, N., Li, W., and Kolaczyk, E. D. 2021 55th Asilomar Conference on Signals, Systems, and Computers, pp. 1268-1273. IEEE.
Uncertainty Quantification in Noisy Networks. (2021) Li, W. Department of Mathematics and Statistics, Boston University.