Research Areas

Editorial Service 

Associate Editor, Bayesian Analysis, Jan 2019-

Associate Editor, new ACM Transactions on Probabilistic Machine Learning, 2023-

Associate Editor, Computational Statistics & Data Analysis, 2024-

Preprints

[53] Ye, S. and Li, M. (2024). Ab initio nonparametric variable selection for scalable Symbolic Regression with large p. arXiv: 2410.13681

[52] Luo, H. and Li, M. (2024). Ranking Perspective for Tree-based Methods with Applications to Symbolic Feature Selection. arXiv: 2410.02623

[51] Liu, Z. and Li, M. (2023). Optimal plug-in Gaussian processes for modeling derivatives. Journal of the American Statistical Association, revision invited. arXiv: 2210.11626

[50] Liu, Y., Li, M. and Morris, J. S. (2024). Scalable Function-on-Scalar Quantile Regression for Densely Sampled Functional Data. Under review. arXiv: 2002.03355

[49] Zeng, Z., Li, M. and Vannucci, M. (2024). Bayesian Covariate-Dependent Graph Learning with a Dual Group Spike-and-Slab Prior. Biometrics, revision invited.

[48] Lin, H. and Li, M. (2023). Valid confidence intervals for regression with best subset selection. Under review. arXiv: 2311.13768 [Code]

[47] Liu, R., Li, K. and Li, M. (2023). Estimation and Hypothesis Testing of Derivatives in Smoothing Spline ANOVA Models. Under review. arXiv: 2308.13905

[46] Liu, X., Wu, Y., Irving, D.L. and Li, M. (2021). Gaussian graphical models with graph constraints for magnetic moment interaction in high entropy alloys. AOAS, R&R. arXiv:2105.05280 [Code]

[45] Liu, Z. and Li, M. (2020). Equivalence of Convergence Rates of Posterior Distributions and Bayes Estimators for Functions and Nonparametric Functionals. arXiv: 2011.13967

[44] Lu, J., Li, M. and Dunson, D. (2018). Reducing Over-clustering via the Powered Chinese Restaurant Process. arXiv:1802.05392.

Forthcoming

[43] Cao, Z., Li, M., Ogilvie, H.A. and Nakhleh, L. (2023+). The Impact of Model Misspecification on Phylogenetic Network Inference. Bulletin of the Society of Systematic Biologists, accepted. [Preprint]

[42] Blackburn, K. W., Green, S. Y., Kuncheria, A., Li, M., Hassan, A. M., Rhoades, B., Weldon, S. A., Chatterjee, S., Moon, M. R., LeMaire, S. A. and Coselli, J. S. (2024+). Predicting operative mortality in patients who undergo elective, open thoracoabdominal aortic aneurysm repair. JTCVS Open, accepted.

[41] Morales-Demori, R., Chen, B., Heinle, J., Li, M. and Anders, M. (2024+). Assessment of B-Natriuretic Peptide Levels After Stage 1 Palliation in Hypoplastic Left Heart Syndrome Patients. Pediatric Cardiology, accepted.

2024

[40] Li, M., Liu, Z., Yu, C.-H. and Vannucci, M. (2024). Semiparametric Bayesian inference for local extrema of functions in the presence of noise. Journal of the American Statistical Association, 119(548), 3127–3140. [Offical link] [Preprint version]

[39] Ye, S., Senftle, P.T. and Li, M. (2024). Operator-induced structural variable selection for identifying materials genes. Journal of the American Statistical Association, 119(545), 81–94. [Code] [R package]

[38] Lamba, H. K., Kim, M., Li, M., Civitello, A. B., Nair, A. P., Simpson, L., Herlihy, J. P., Frazier, O. H., Rogers, J. G., Loor, G., Liao, K. K., Shafii, A. E. and Chatterjee, S. (2024). Predictors and Impact of Prolonged Vasoplegia after Continuous-flow Left Ventricular Assist Device Implantation. Journal of the American College of Cardiology: Advances, 3(5), 100916.

[37] Zeng, Z., Li, M. and Vannucci, M. (2024). Bayesian Image-on-Scalar Regression with a Spatial Global-Local Spike-and-Slab Prior. Bayesian Analysis, 19(1), 235–260. [Code]

[36] Liu, R., Li, M. and Ma, L. (2024). Efficient in-situ image and video compression through probabilistic image representation. Signal Processing, 215, 109268. [Code] (This is the journal version of our previous CVPR paper)

[35] Yu, C.-H., Li, M. and Vannucci, M. (2024). Semiparametric Latent ANOVA Model for Event-Related Potentials. Data Science in Science, 3(1), 2294204. [Code]

[34] Mohammadi, M. and Li, M. (2024). Model-free prediction of time series: a nonparametric approach. Journal of Nonparametric Statistics,36(3), 804–824.

[33] Pluta, D., Hadj-Amar, B., Li, M., Zhao, Y., Versace, F. and Vannucci. M. (2024). Improved data quality and statistical power of trial-level event-related potentials with Bayesian random-shift Gaussian processes. Scientific Reports, 14, 8856.

[32] Li, G., Liu, Z., Salan-Gomez, M., Keeney, E., D’Silva, E., Mankidy, B., Leon, A., Mattar, A., Elsennousi, A., Coster, J., Kumar, A., Rodrigues, B., Li, M., Shafii, A., Garcha, P. and Loor, G. (2024). Risk Factors, Incidence, and Outcomes Associated with Clinically Significant Airway Ischemia. Transplant International, 37, 12751.

2023

[31] Liu, Z. and Li, M. (2023). On the Estimation of Derivatives Using Plug-in Kernel Ridge Regression Estimators. Journal of Machine Learning Research, 24(266):1–37.

[30] Liu, R., Li, M. and Dunson D. (2023). PPA: Principal Parcellation Analysis for Brain Connectomes and Multiple Traits. NeuroImage, 276, 120214. [Code]

[29] Wang, Z., Magnotti, J., Beauchamp, M. and Li, M. (2023). Functional Group Bridge for Simultaneous Regression and Support Estimation. Biometrics, 79(2), 1226–1238. [R package][Data]

[28] Yu, C.-H., Li, M., Noe, C., Fischer-Baum, S. and Vannucci, M. (2023). Bayesian Inference for Stationary Points in Gaussian Process Regression Models with Applications to Event-Related Potentials Analysis. Biometrics, 79(2), 629–641.

[27] Edrisi, M., Ogilvie, H.A., Li, M. and Nakhleh, L. (2023). MoTERNN: Classifying the Mode of Cancer Evolution Using Recursive Neural Networks, RECOMB-CG 2023: Comparative Genomics (International Conference on Research in Computational Molecular Biology), 232–247, 2023.

[26] Ryan, C.T., Zeng, Z., Chatterjee, S., Wall, M.J., Moon, M.R., Coselli, J.S., Rosengart T.K., Li, M., and Ghanta, R.K. (2023), Machine Learning for Dynamic and Early Prediction of Acute Kidney Injury after Cardiac Surgery. The Journal of Thoracic and Cardiovascular Surgery, 166(6), e551–e564.

[25] Beroukhim, K., Williams, P.H., Goldberg, L.H., Bovenberg, M.S., Tan, X., Li, M., Hall, E., Tarantino, I. and Hamel, R. (2023). A Prospective, Randomized Controlled, Single-Blinded Study to Assess the Effect of a 33-Gauge Needle Versus a 34-Gauge Needle on Pain Experienced During Injection of Local Anesthetic on the Face. Journal of Drugs in Dermatology: JDD, 22(11), 1124–1127.

[24] Chacon-Alberty, L., Ye, S., Elsenousi, A., Hills, E., King, M., D’vya, E., Leon, A. P., Salan-Gomez, M., Li, M., Hochman-Mendez, C., and Loor, G. (2023). Effect of intraoperative support mode on circulating inflammatory biomarkers after lung transplantation surgery. Artificial Organs, 47(4), 749–760.

2022

[23] Li, M. and Ma, L. (2022). Learning Asymmetric and Local Features in Multi-Dimensional Data through Wavelets with Recursive Partitioning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(11), 7674–7687. [Matlab code][R package]

[22] Lin, H. and Li, M. (2022). Double spike Dirichlet priors for structured weighting. Journal of Machine Learning Research, 23(248):1−28. [Code]

[21] Chacon-Alberty, L., Kanchi, R.S., Ye, S., Hochman-Mendez, C., Daoud, D., Coarfa, C., Li, M., Grimm, S.L., Baz, M., Rosas, I., and Loor, G. (2022). Plasma protein biomarkers for primary graft dysfunction after lung transplantation: a single-center cohort analysis. Scientific Reports, 12, 16137.

[20] Liu, C.-Y., Ye, S., Li, M. and Senftle, P.T. (2022). A Rapid Feature Selection Method for Catalyst Design: Iterative Bayesian Additive Regression Trees (iBART). Journal of Chemical Physics, 156, 164105.

[19] Li, M., Wang, K., Maity, A. and Staicu, A.M. (2022). Inference in Functional Linear Quantile Regression. Journal of Multivariate Analysis, 190, 104985. [R Code]

[18] O’Neil, E.R., Lin, H., Shamshirsaz, A.A., Naoum, E.E., Rycus, P.R., Alexander, P.M., Ortoleva, J.P., Li, M. and Anders, M.M. (2022). Pregnant/Peripartum Women with COVID-19 High Survival with ECMO: An ELSO Registry Analysis. American Journal of Respiratory and Critical Care Medicine, 205(2), 248–250.

2021

[17] Zeng, Z. and Li, M. (2021). Bayesian Median Autoregression for Robust Time Series Forecasting. International Journal of Forecasting, 37(2), 1000–1010. [Code]

[16] Chacon-Alberty, L., Ye, S., Daoud, D., Frankel, W.C., Virk, H., Mase, J., Hochman-Mendez, C., Li, M., Sampaio, L.C., Taylor, D.A. and Loor, G. (2021). Analysis of Sex-based Differences in Clinical and Molecular Responses to Ischemia Reperfusion after Lung Transplantation. Respiratory Research, 22(1), 318.

[15] O’Neil, E.R., Lin, H., Li, M., Shekerdemian, L., Tonna, J.E., Barbaro, R.P., Abella, J.R., Rycus, P., MacLaren, G., Anders, M. and Alexander, P.M. (2021). ECMO Support for Influenza A: Retrospective Review of the ELSO Registry Comparing Seasonal and Pandemic Subtypes. Critical Care Explorations, 3(12), e0598.

[14] Lin, Y., Saboo, A., Frey, R., Sorkin, S., Gong, J., Olson, G.B., Li, M. and Niu, C. (2021). CALPHAD Uncertainty Quantification and TDBX. JOM, 73, 116–125.

2020

[13] Li, M. and Dunson, D. (2020). Comparing and weighting imperfect models using D-probabilities. Journal of the American Statistical Association, 115, 1349–1360. [R code]

[12] Liu, C.-Y., Zhang, S., Martinez, D., Li, M. and Senftle, P. T. (2020). Using Statistical Learning to Predict Interactions Between Single Metal Atoms and Modified MgO(100) Supports. npj Computational Materials, 6,102.

[11] Liu, R., Li, M. and Ma, L. (2020). CARP: Compression through Adaptive Recursive Partitioning for Multi-dimensional Images. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 14306–14314. [Code]

[10] Liu, Y., Li, M. and Morris, J. S. (2020). Function-on-Scalar Quantile Regression with Application to Mass Spectrometry Proteomics Data. Annals of Applied Statistics, 14(2), 521–541. [Code]

[9] Li, M. and Goldman, R. (2020). Limits of Sums for Binomial and Eulerian Numbers and their Associated Distributions. Discrete Mathematics, 343(7), 11870. 

[8] Tang, W. and Li, M. (2020). Scalable Double Regularization for 3D Nano-CT Reconstruction. Journal of Petroleum Science and Engineering, 192, 107271. [Matlab code]

2018

[7] Li, M. and Schwartzman, A. (2018). Standardization of Multivariate Gaussian Mixture Models for Background Adjustment of PET Images in Brain Oncology. Annals of Applied Statistics, 12(4), 2197–2227.

[6] Li, M. (2018). Invited discussion of “Using Stacking to Average Bayesian Predictive Distributions” by Yuling Yao, Aki Vehtari, Daniel Simpson, and Andrew Gelman. Bayesian Analysis, 13(3), 951–956.

2017

[5] Li, M. and Ghosal, S.(2017). Bayesian Detection of Image Boundaries. Annals of Statistics, 45(5), 2190–2217.

[4] Syring N. and Li, M. (2017). BayesBD: An R Package for Bayesian Inference on Image Boundaries. R Journal, 9(2), 149–162.

2014-2015

[3] Li, M., Staicu, A.M. and Bondell, H. (2015). Incorporating Covariates in Skewed Functional Data Models. Biostatistics, 16(3), 413–426.

[2] Li, M. and Ghosal, S.(2015). Fast Translation Invariant Multiscale Image Denoising. IEEE Transactions on Image Processing, 12(24), 4876–4887.

[1] Li, M. and Ghosal, S.(2014). Bayesian Multiscale Smoothing of Gaussian Noised Images. Bayesian Analysis, 9(3), 733–758.