Publications and Presentations

Journal Papers

2025

[student paper] Wei, G.Z., Qiu, F., and Liu, X., (2025), “Convolutional Non-Homogeneous Poisson Process and its Application to Wildfire Ignition Risk Quantification for Power Delivery Networks”, Technometrics, 67, 11-22. Article Link. (also on arXiv:2301.00067).
Liu, X., Feng, J.Y., and Liu, X.C., (2025), "Adapting Projection-Based Reduced-Order Models using Projected Gaussian Process", under revision. arXiv: 2410.14090. Article Link.
[student paper] Shi, H.Z., Wang, Y.H. and Liu, X. (2025), "Fire-EnSF: Wildfire Spread Data Assimilation using Ensemble Score Filter", arXiv:2510.15954. Article Link.
Wang, Y.S., Zeng, Q., Liu, X., and Ding, Y. (2025), "Mutual Information Surprise: Rethinking Unexpectedness in Autonomous Systems", arXiv:2508.17403. Article Link.
Lin, Z.Z., Hong, Y.L., Liu, X., and Xiang, Y.S., (2025), "Modeling Multivariate Degradation Data with Dynamic Covariates Under Bayesian Framework", Reliability Engineering and Systems Safety, 261, 111115. Article Link. (also on arXiv:2504.05484).
[student paper] Liu, X.C., Hwang, Y., Phan, D., Klein, L. Liu, X., Yeo, K., (2025), "Sparse Sensor Allocation for Inverse Problems of Detecting Sparse Leaking Emission Sources", IISE Transactions (accepted), arXiv:2509.05559. Article Link.
[student paper] Iranzad, R., Liu, X. (2025), “A Review of Random-Forests-Based Feature Selection Methods for Data Science Education and Applications”, International Journal of Data Science and Analytics, 20, 197–211. Article Link.

2023-2024

[student paper] Wei, G.Z., Krishnan, V., Xie, Y., Sengupata, M., Zhang, Y.C., Liao, H.T., and Liu, X., (2024), "A Statistical Model for Multi-Source Remote-Sensing Data Streams of Wildfire Aerosols Optical Depth," INFORMS Journal on Data Science, 3, 162-178. Article Link. (also on arXiv: 2206.11766).
[student paper] Iranzad, R., Liu, X., Dese, K., Alkhadrawi, H., Snoderly, H., and Bennewitz, M., (2024), "Structured Adaptive Boosting Trees for Detection of Multicellular Aggregates in Fluorescence Intravital Microscopy", Microvascular Research, 156, 104732. Article Link.
[student paper] Wei, G.Z., Liu, X., and Barton, R. (2024), “An extended PDE-based statistical spatio-temporal model that suppresses the Gibbs phenomenon”, Environmetrics, 35, e2831. Article Link.
Liu, X., and Yeo, K.M. (2023), “Inverse Model for Estimating the Initial Condition of Spatio-Temporal Advection-Diffusion Processes”, Technometrics, 65, 432-445. Article Link. code. (also on arXiv: 2302.04134).
[student paper] Liu, X.C., Liu, X., Kaman, T, Lu, X., and Lin, G. (2023), “Statistical Learning for Nonlinear Dynamical Systems with Applications to Aircraft-UAV Collisions”, Technometrics, 65, 564-578. Article Link.
[student co-author] Liu, X., and Liu, X.C. (2023), “Regression Trees on Grassmann Manifold for Adapting Reduced-Order Models”, AIAA Journal (American Institute of Aeronautics and Astronautics), 61(3), 1318-1333. Article Link. (also on arXiv: 2206.11324).

2020-2022

Liu, X., Yeo, K. M., Lu, S. Y. (2022), “Statistical Modeling for Spatio-Temporal Data from Stochastic Convection-Diffusion Processes”, Journal of the American Statistical Association (Theory and Methods), 117, 1482-1499. Article Link. code. (also on arXiv: 1910.10375).
[student author] Iranzad, R., Liu, X., Chaovalitwongse, W. A., Hippe, D. S., Wang, S., Han, J., Thammasorn, P., Duan, C.Y., Zeng, J., Bowen, S. R. (2022), "Gradient boosted trees for spatial data and its application to medical imaging data", IISE Transactions on Healthcare Systems Engineering, 12, 165-179. Article Link.
Forouzannezhad, P., Maes, D., Hippe, D., Thammasorn, P., Iranzad, R., Han, J., Duan, C., Liu, X., Wang, S., Chaovalitwongse, W., Zeng, J., Bowen, S. (2022), "Multitask Learning Radiomics on Longitudinal Imaging to Predict Survival Outcomes following Risk-Adaptive Chemoradiation for Non-Small Cell Lung Cancer", Cancers, Special Issue Medical Imaging and Machine Learning, 14, 1288. Article Link.
[student author] Hajiha, M., Liu, X., Lee, Y., and Moghaddass, R. (2022) "A Physics-Regularized Data-Driven Approach for Health Prognostics of Complex Engineered Systems with Dependent Health States", Reliability Engineering and System Safety, Special Issue--Physics-Informed Machine Learning for Reliability and Safety, 226, 108677. Article Link.
Liu, X., (2022), Book Review "Statistical Machine Learning–A Unified Framework: Richard Golden. Chapman & Hall/CRC, Boca Raton, FL, 2020, 102.16hardcover, 90.46 eBook, ISBN 978-1138484696", Journal of Quality Technology 54 (5), 605-605. Article Link.
Liu, X., and Pan, R. (2021), "Boost-R: Gradient Boosting for Recurrent Event Data", Journal of Quality Technology, Special Issue-Artificial Intelligence & Statistics for Quality Technology, 53, 545-565. Article Link. code. (also on arXiv:2107.08784).
[student author] Hajiha, M., Liu, X., and Hong, Y. (2021), “Degradation under Dynamic Operating Conditions: Modeling, Competing Processes and Applications ”, Journal of Quality Technology, 53, 347-368. Article Link.
Liu, X., (2021), “A Simple Procedure for Analyzing Reliability Data from Double-Stage Accelerated Life Tests”, Quality Technology and Quantitative Management, 18, 67-82. Article Link. code.
Liu, X., and Pan, R. (2020), "Analysis of Large Heterogeneous Repairable System Reliability Data with Static System Attributes and Dynamic Sensor Measurement in Big Data Environment", Technometrics, 62, 206-222. Article Link. code. (also on arXiv:1904.01128).
Duan, C., Chaovalitwongse, W. A., Bai, F., Hippe, D., Wang, S., Thammasorn, P., Pierce, L. A., Liu, X., You, J., Miyaoka, R. S., Vesselle, H.J., Kinahan, P.E., Rengan, R., Zeng, J., and Bowen, S.R. (2020), "Sensitivity analysis of FDG PET tumor voxel cluster radiomics and dosimetry for predicting mid-chemoradiation regional response of locally advanced lung cancer", Physics in Medicine & Biology, DOI: 10.1088/1361-6560/abb0c7. Article Link.
S Bowen, D Hippe, W Chaovalitwongse, P Thammasorn, X Liu, R Iranzad, R Miyaoka, H Vesselle, P Kinahan, R Rengan, J Zeng, (2021), "Voxel Forecast Classifier to Predict Spatially Variant Binary Tumor Voxel Response On Longitudinal FDG-PET/CT Imaging of FLARE-RT Protocol Patients", Medical Physics, 47, E672-E672. Article Link.

Before 2020

Yeo, K.M., Hwang, Y.D., Liu, X., and Kalagnanam, J. (2019), "Development of hp-inverse model by using generalized polynomial chaos", Computer Methods in Applied Mechanics and Engineering, 347, 1-20. Article Link.
Bowen. S, Hippe, D, Chaovalitwongse, W. A., Duan, C., Thammasorn, P., Liu, X., Miyaoka, R., Vesselle, H., Kinahan, P., Rengan, R., and Zeng, J., (2019), "Forecast for Precision Oncology: predicting spatially variant and multiscale cancer therapy response on longitudinal quantitative molecular imaging," Clinical Cancer Research, 25(16), 5027-5037. Article Link.
Liu, X., Gopal, V., and Kalagnanam, J. (2018), "A Spatio-Temporal Modeling Framework for Weather Radar Image Data in Tropical Southeast Asia", Annals of Applied Statistics, 12(1), 378–407. Article Link. code. (also available on arXiv:1609.09816).
Liu, X., Yeo, K.M. and Kalagnanam, J. (2018), "A Statistical Modeling Approach for Spatio-Temporal Degradation Data", Journal of Quality Technology, 50, 166--182. Special issue on "reliability and maintenance modeling with big data". Article Link. (also available on arXiv:1609.07217).
Liu, X., Yeo, K.M., Hwang, Y.D., Singh, J. and Kalagnanam, J. (2016) "A Statistical Modeling Approach for Air Quality Data Based on Physical Dispersion Processes and Its Application to Ozone Modeling", Annals of Applied Statistics, 10(2), 756-785. Article Link.
Liu, X. and Tang, L.C. (2016) "Reliability Analysis and Spares Provisioning for Repairable Systems with Dependent Failure Processes and Time-Varying Installed Base", IIE Transactions, 48, 43--56. (Featured in Industrial Engineer Magazine Dec 2015). Article Link.
Yeo, K., Hwang, Y., Liu, X. and Kalagnanam, J. (2016), "Stochastic Optimization Algorithm for Inverse Modeling of Air Pollution", Bulletin of the American Physical Society, 61. Article Link.
Singh, J., Yeo, K., Liu, X., Hosseini, R., and Kalagnanam, J. (2016), "Evaluation of WRF model seasonal forecasts for tropical region of Singapore", Advanced in Science and Research, 12, 69-72. Article Link.
Liu, X., Al-Khalifa. K., Elsayed, A.E., Coit, D.W, and Hamouda, A.M. (2014) "Criticality Measures for Components with Multi-Dimensional Degradation", IIE Transactions, 46, 987–998. Article Link.
Liu, X. and Tang, L.C. (2013) "Planning Accelerated Life Tests with Scheduled Inspections for Log-Location-Scale Distributions", IEEE Transactions on Reliability, 62(2), 515 - 526. Article Link.
Liu, X. (2012) "Planning of Accelerated Life Tests with Dependent Failure Modes Based on a Gamma Frailty Model", Technometrics, 54(4), 398-409. AMSTATNEWS: http://magazine.amstat.org/blog/2012/11/01/design-and-model-selection/. Article Link.
Liu, X., Li, J.R., Al-Khalifa. K., Hamouda, A.M., Coit, D.W, and Elsayed, A.E., (2012) "Condition-Based Maintenance for Continuously Monitored Degrading Systems with Multiple Failure Modes", IIE Transactions, 45, 422-435, (Featured in Industrial Engineer Magazine, Mar 2013). Article Link.
Liu, X.and Tang, L.C. (2012) "Analysis for Reliability Experiments under Blocking", Quality Technology and Quantitative Management, Special Issue: Reliability Modeling, Inference and Analysis, 10, 141-160. Article Link.
Liu, X. and Qiu, W.S. (2011) "Modelling and Planning of Step-Stress Accelerated Life Tests with Independent Competing Risks", IEEE Transactions on Reliability, 60(4), 712-720. Top accessed article of the journal in Jan 2012 (rank:2) Article Link.
Liu, X. and Tang, L.C. (2010) "Accelerated Life Test Plans for Repairable Systems with Multiple Independent Risks", IEEE Transactions on Reliability, 59(1), 115-127. (2010 National Semiconductor Gold Medal, ISE Department, National University of Singapore). Article Link.
Tang, L.C. and Liu, X.(2010) "Planning and Inference for a Sequential Accelerated Life Test", Journal of Quality Technology, 42(1), 103-118. Article Link.
Liu, X. and Tang, L.C. (2010) "A Bayesian Optimal Design for Accelerated Degradation Tests", Quality and Reliability Engineering International, 26(8), 863-875. Special Issue: Business and Industrial Statistics: Developments and Industrial Practices in Quality and Reliability. Article Link.
Liu, X. and Tang, L.C. (2010) "Planning Sequential Constant-Stress Accelerated Life Tests with Stepwise Loaded Auxiliary Acceleration Factor", Journal of Statistical Planning and Inference, 140(7), 1968-1985. Article Link.
Liu, X. and Tang, L.C. (2009) "A Sequential Constant-Stress Accelerated Life Testing Scheme and Its Bayesian Inference", Quality and Reliability Engineering International, 25(1), 91-109. Article Link.

Patent

US Patent 10,607,145: "Detection algorithms for distributed emission sources of abnormal events". (Y HWANG, JR Kalagnanam, X Liu, KM Yeo)
US Patent 9,995,849: "Airborne particulate source detection system" (J Kalagnanam, L Xiao, KM Yeo, Y Zhou)

Book Chapters

He, Y.Q., Huang, M.Q., Shahpar, S., Wei, G.Z., Liu, X., Wang, Z.S., (2025+), "Weather-related Disasters", to appear in Data-Driven Earth Observation for Disaster Management, Elsevier.
Liu, X., and Hajiha, M., (2022), "A Physics-Regularized Degradation Model for Cooling System Health Management", in Handbook of Smart Energy Systems, Mahdi Fathi, Enrico Zio, Panos Pardalos (Eds.), Springer.

Invited Seminars

2025

"Real time wildfire predictive and management capabilities", Climate Tech Showcase, New York Climate Week, Sep 2025.
"Adaptive Reduced-Order Modeling using Statistical Learning", 2025 Zorich’s Applied Statistics Workshop, Texas A&M University, Sep 2025.
"Statistical Learning for Adaptive Reduced-Order Modeling", Department of Industrial Systems Engineering and Management, National University of Singapore, July 2025.
"Adaptive Reduced-Order Modeling using Statistical Learning", Department of Mathematics, Florida State University, Apr 2025.

Before 2025

"Statistical Learning for Spatio-Temporal Environmental and Event Processes", 4TU.Resilience Engineering, TU Delft, Netherlands, July 2024.
“Statistical Learning for Scientific and Engineering Processes”, Department of Mathematical and Statistical Sciences, Clemson University, Apr 2024.
"Statistical Learning for Scientific and Engineering Processes", QSR INFORMS Webinar, 2024.
"Domain-Aware Statistical Learning – Harnessing the Convergence of Engineering Knowledge and Data-Driven Methods", Department of Industrial Systems Engineering and Management, National University of Singapore, Aug 2023.
"Domain-Aware Statistical Learning for Natural and Engineering Processes", Department of Industrial and Systems Engineering, University of Washington, Apr 2022.
“Spatio-Temporal Statistical Models for Physical Convection-Diffusion Processes”, Harold and Inge Marcus Department of Industrial and Manufacturing Engineering, Penn State, Oct 2021.
Department of Aerospace and Mechanical Engineering, University of Oklahoma, Feb 11, 2021 (virtual).
“Physics-Informed Statistical Models for Physical/Engineering Processes”, Department of Industrial and Management Systems Engineering, University of South Florida, Nov 23, 2020 (virtual).
“Analysis of Large Heterogeneous Repairable System Reliability Data in Big Data Environment”, IISE DAIS Division, Webinar, Nov, 2018.
"Analysis of Large Heterogeneous Repairable System Reliability Data with Covariates in Big Data Environment", Department of Systems Engineering and Engineering Management, City University of Hong Kong, July 2018.
School of Reliability and Systems Engineering, Beihang University, Jun 2018.
"Modeling of Spatio-Temporal Data and Some Applications", Department of Mathematical Sciences, J. William Fulbright College of Arts & Sciences, University of Arkansas, Apr 2018.
"On the modeling of spatio-temporal data", IE, Peking University, July 2017.
"Spatio-Temporal Degradation Models", SSIE, SUNY Binghamton, Apr 2017.
"A Statistical Modeling Approach for Spatio-Temporal Data and Its Applications", ISE, Rutgers University, Oct 2016.
"A Statistical Modeling Approach for Spatio-Temporal Data and Its Applications", ISyE, GeorgiaTech, Sep 2016.
"Analytical Models for Condition-Based Maintenance under Dynamic Environments", School of Computer Engineering, Nanyang Technological University, Singapore.
"Reliability Modeling and Condition-Based Maintenance," Texas A&M University at Qatar (TAMUQ) and ConocoPhillips Annual Qatar Process Safety Symposium, Doha, Qatar, Mar, 2012. (http://www.gulf-times.com/site/topics/article.asp?cu_no=2&item_no=493326&version=1&template_id=36&parent_id=16)
Liu, X, "An Introduction to Condition-Based Maintenance" American Society for Quality (ASQ) Chinese Reliability Webinar Series, Apr. 11, 2012. (http://www.reliabilitycalendar.org/The_Reliability_Calendar/Webinars_-_Chinese/Webinars_-_Chinese.html)
"Advances in Modeling, Planning and Analysis of Accelerated Life Tests," Department of Industrial and Systems Engineering, Auburn University, Alabama, USA, Feb 1, 2012.
"New Developments in Accelerated Reliability Testing and Spares Provisioning for System Maintenance," Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, Jan 31, 2011, Eindhoven, Netherlands.
"Planning of Accelerated Life Tests under Non-Destructive Intermittent Inspections," Department of Applied Probability and Statistics, National University of Singapore, Dec 22, 2010, Singapore.

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