My research interests are in Bayesian Statistics and more specifically applications, scalable computation and related theory, and Gaussian graphical models. Additionally, I try to advance clinical knowledge by working on medical records data in close collaboration with clinicians.


Qian, F., van den Boom, W., and See, K.C. (2024). The new global definition of acute respiratory distress syndrome: Insights from the MIMIC-IV database. Intensive Care Medicine, 50(4), 608–609. doi:10.1007/10.1007/s00134-024-07383-x

Saini, S., Manai, G., van den Boom, W., De Iorio, M., and Qian, F. (2024). Invoice level forecasting with discrete survival methods for effective forecasting of account receivables in supply chain. Discover Analytics, 2, 5. doi:10.1007/s44257-024-00013-2

Natarajan, A., van den Boom, W., Odang, K.B., and De Iorio, M. (2024). On a wider class of prior distributions for graphical models. Journal of Applied Probability, 61(1), 230–243. doi:10.1017/jpr.2023.33

Feng, S.F., van den Boom, W., De Iorio, M., Thng, G.J., Chan, J.K.Y., Chen, H.Y., Tan, K.H., and Kee, M.Z.L. (2024). Joint modelling of mental health markers through pregnancy: A Bayesian semi-parametric approach. Journal of Applied Statistics, 51(2), 388–405. doi:10.1080/02664763.2022.2154329

van den Boom, W., De Iorio, M., and Beskos, A. (2023). Bayesian learning of graph substructures. Bayesian Analysis, 18(4), 1311–1339. doi:10.1214/22-BA1338

van den Boom, W., De Iorio, M., Beskos, A., and Jasra, A. (2023). Graph sphere: From nodes to supernodes in graphical models. doi:10.48550/arXiv.2310.11741

Qian, F., van den Boom, W., and See, K.C. (2023). Real-world evidence challenges controlled hypoxemia guidelines for critically ill patients with chronic obstructive pulmonary disease. Intensive Care Medicine, 49(9), 1133–1135. doi:10.1007/s00134-023-07166-w

van den Boom, W., De Iorio, M., Qian, F., and Guglielmi, A. (2023). The Multivariate Bernoulli detector: Change point estimation in discrete survival analysis. doi:10.48550/arXiv.2308.10583

Young, A.L., van den Boom, W., Schroeder, R.A., Krishnamoorthy, V., Raghunathan, K., Wu, H.T., and Dunson, D.B. (2023). Mutual information: Measuring nonlinear dependence in longitudinal epidemiological data. PLOS ONE, 18(4), e0284904. doi:10.1371/journal.pone.0284904

Franzolini, B., Cremaschi, A., van den Boom, W., and De Iorio, M. (2023). Bayesian clustering of multiple zero-inflated outcomes. Philosophical Transactions of the Royal Society A, 381(2247), 20220145. doi:10.1098/rsta.2022.0145

van den Boom, W., Beskos, A., and De Iorio, M. (2022). The G-Wishart weighted proposal algorithm: Efficient posterior computation for Gaussian graphical models. Journal of Computational and Graphical Statistics, 31(4), 1215–1224. doi:10.1080/10618600.2022.2050250 pdf

van den Boom, W., Jasra, A., De Iorio, M., Beskos, A., and Eriksson, J.G. (2022). Unbiased approximation of posteriors via coupled particle Markov chain Monte Carlo. Statistics and Computing, 32(3), 36. doi:10.1007/s11222-022-10093-3 pdf

van den Boom, W., De Iorio, M., and Tallarita, M. (2022). Bayesian inference on the number of recurrent events: A joint model of recurrence and survival. Statistical Methods in Medical Research, 31(1), 139–153. doi:10.1177/09622802211048059

Lysaght, T., Ballantyne, A., Toh, H.J., Lau, A., Ong, S., Schaefer, O., Shiraishi, M., van den Boom, W., Xafis, V., and Tai, E.S. (2021). Trust and trade-offs in sharing data for precision medicine: A national survey of Singapore. Journal of Personalized Medicine, 11(9), 921. doi:10.3390/jpm11090921

van den Boom, W., Reeves, G., and Dunson, D.B. (2021). Approximating posteriors with high-dimensional nuisance parameters via integrated rotated Gaussian approximation. Biometrika, 108(2), 269–282. doi:10.1093/biomet/asaa068 pdf

van den Boom, W., Hoy, M., Sankaran, J., Liu, M., Chahed, H., Feng, M., and See, K.C. (2020). The search for optimal oxygen saturation targets in critically ill patients: Observational data from large ICU databases. Chest, 157(3), 566–573. doi:10.1016/j.chest.2019.09.015

van den Boom, W., Mao, C., Schroeder, R.A., and Dunson, D.B. (2018). Extrema-weighted feature extraction for functional data. Bioinformatics, 34(14), 2457–2464. doi:10.1093/bioinformatics/bty120

van den Boom, W., Schroeder, R.A., Manning, M.W., Setji, T.L., Fiestan, G., and Dunson, D.B. (2018). Effect of A1C and glucose on postoperative mortality in noncardiac and cardiac surgeries. Diabetes Care, 41(4), 782–788. doi:10.2337/dc17-2232

van den Boom, W., Dunson, D., and Reeves, G. (2015). Quantifying uncertainty in variable selection with arbitrary matrices. IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), pp. 385–388. doi:10.1109/CAMSAP.2015.7383817

van den Boom, W., Reeves, G. and Dunson, D.B. (2015). Scalable approximations of marginal posteriors in variable selection. doi:10.48550/arXiv.1506.06629