Journals and Transactions

[1] Liu, K., and Shi, J. (2013), “Objective-Oriented Optimal Sensor Allocation Strategy for Process Monitoring and Diagnosis by Multivariate Analysis in a Bayesian Network”, IISE Transactions, 45, 630–643.
[2] Jin, R., and Liu, K. (2013), “Multistage Multimode Process Monitoring Based on a Piecewise Linear Regression Tree Considering Modeling Uncertainty”, IISE Transactions, 45, 617-629.
[3] Liu, K., Gebraeel, N., and Shi, J. (2013), “A Data-Level Fusion Model for Developing Composite Health Indices for Degradation Modeling and Prognostic Analysis”, IEEE Transactions on Automation Science and Engineering, 10, 652 – 664. (This paper received Best Student Paper Award in Data Mining Section of INFORMS, 2012)
[4] Liu, K., Jain, S., and Shi, J. (2013), “Physician Performance Assessment Using a Composite Quality Index”, Statistics in Medicine, 32, 15, 2661-2680. (This paper received Best Student Paper Award Finalist in Quality, Statistics, and Reliability Section of INFORMS, 2012)
[5] Liu, K., Zhang, X., and Shi, J. (2014), “Adaptive Sensor Allocation Strategy for Process Monitoring and Diagnosis in a Bayesian Network”, IEEE Transactions on Automation Science and Engineering, 11, 2, 452-462. (This paper received Best Student Paper Award in the Industrial and Systems Engineering Research Conference (ISERC), 2013)
[6] Liu, K., Mei, Y., and Shi, J. (2015), “An adaptive sampling strategy for online high-dimensional process monitoring”, Technometrics, 57, 3, 305-319.
[7] Liu, K., and Shi, J. (2015), “A Systematic Approach for Business Data Analytics with a Real Case Study”, International Journal of Business Analytics (IJBAN), 2, 4, 23-44.
[8] Liu, K., and Shi, J. (2015), “Internet of Things (IoT)-enabled System Informatics for Service Decision Making: Achievements, Trends, Challenges, and Opportunities”, IEEE Intelligent Systems, 30, 6, 18-21.
[9] Zhou, C., Liu, K., Zhang, X., Zhang, W., and Shi, J. (2016), "An Automatic Process Monitoring Method Using Recurrence Plot in Progressive Stamping Processes", IEEE Transactions on Automation Science and Engineering, 13, 2, 1102 - 1111.
[10] Song, C.*, Liu, K., Zhang, X., Chen, L., and Xian, X.* (2016), “An OSA Screening Approach Using Discriminative Hidden Markov Models from a Single ECG Lead”, IEEE Transactions on Biomedical Engineering, 63, 7, 1532 - 1542. (This paper received the Best Student Paper Finalist in the Industrial and Systems Engineering Research Conference (ISERC), 2015)
[11] Liu, K., and Huang, S. (2016), “Integration of Data Fusion Methodology with Degradation Modeling Process to Improve Prognostics”, IEEE Transactions on Automation Science and Engineering, 13, 1, 344 - 354.
[12] Yan, H., Liu, K., Zhang, X., and Shi, J. (2016), “Multiple Sensor Data Fusion for Degradation Modeling and Prognostics under Multiple Operational Conditions”, IEEE Transactions on Reliability, 65, 3, 1416 - 1426.
[13] Hao, L., Liu, K., Gebraeel, N., and Shi, J. (2017), “Controlling the Residual Life Distribution of Parallel Multi-component Systems Through Workload Adjustment”, IEEE Transactions on Automation Science and Engineering, 14, 2, 1042 - 1052.
[14] Liu, K., Chehade, A.*, and Song, C.* (2017), “Optimize the Signal Quality of the Composite Health Index via Data Fusion for Degradation Modeling and Prognostic Analysis”, IEEE Transactions on Automation Science and Engineering, 63, 7, 1532 - 1542. (This paper received the Best Student Poster award in Quality, Statistics, and Reliability Section of INFORMS, 2015)
[15] Li, J., Liu, K., and Xian, X.* (2017), “Causation-based Process Monitoring and Diagnosis for Multivariate Categorical Processes”, IISE Transactions, 49, 3, 332-343. (Feature article in IIE Magazine)
[16] Chehade, A.*, Bonk, S.*, and Liu, K. (2017), “Sensory-based Failure Threshold Estimation for Remaining Useful Life Prediction”, IEEE Transactions on Reliability, 66, 3, 939-949
[17] Xian, X.*, Wang, A.*, and Liu, K. (2018), “A Nonparametric Adaptive Sampling Strategy for Online Monitoring of Big Data Streams”, Technometrics, 60, 1, 14-25. (This paper received the Best Student Poster award in Quality, Statistics, and Reliability Section of INFORMS, 2016)
[18] Song, C.*, Liu, K., and Zhang, X. (2018), “Integration of Data-level Fusion Model and Kernel Methods for Degradation Modeling and Prognostic Analysis”, IEEE Transactions on Reliability, 67, 2, 640-650.
[19] Chehade, A.*, Song, C.*, Liu, K., Saxena, A., and Zhang, X. (2018), “A Data-level Fusion Approach for Degradation Modeling and Prognostic Analysis under Multiple Failure Modes”, Journal of Quality Technology, 50, 2, 150-165. (This paper received the Best Student Paper Finalist award (2nd place) in the QCRE Section of Industrial and Systems Engineering Research Conference (ISERC), 2016).
[20] Lin, Y., Liu, K., Byon, E., Qian, X., and Huang, S. (2018), “A Collaborative Learning Framework for Estimating Many Individualized Regression Models in a Heterogeneous Population”, IEEE Transactions on Reliability, 67, 1, 328-341.
[21] Xian, X.*, Archibald, R., Mayer, B., Liu, K., and Li, J. (2019), “An Effective Online Data Monitoring and Saving Strategy for Large-Scale Climate Simulations”, Quality Technology & Quantitative Management, 16, 3, 330-346.
[22] Wang, A.*, Xian, X.*, Tsung, F., and Liu, K. (2018), “A Spatial Adaptive Sampling Procedure for Online Monitoring of Big Data Streams”, Journal of Quality Technology, 50, 4, 329-343.
[23] Song, C.*, and Liu, K. (2018), “Statistical Degradation Modeling and Prognostics of Multiple Sensor Signals via Data Fusion: A Composite Health Index Approach”, IISE Transactions, 50, 10, 853-867. (This paper received the Best Paper Finalist award (theoretical track) in the Data Mining Section of INFORMS, 2017).
[24] Chehade, A.*, and Liu, K. (2019), “Structural Degradation Modeling Framework for Sparse Datasets with an application on Alzheimer’s Disease”, IEEE Transactions on Automation Science and Engineering, 16, 1, 192 - 205. (This paper receives the Best New Application Paper Award (first runner-up) in IEEE Transactions on Automation Science and Engineering, 2020)
[25] Wang, D., Liu, K., and Zhang, X. (2019), “Modeling of a three-dimensional dynamic thermal field under grid-based sensor networks in grain storage”, IISE Transactions, 51, 5, 531-546. (Feature article in ISE Magazine; This paper receives the Best Application Paper in IISE Transactions, 2020)
[26] Xian, X.*, Li, J., and Liu, K. (2019), “Causation-based Monitoring and Diagnosis for Multivariate Categorical Processes with Ordinal Information”, IEEE Transactions on Automation Science and Engineering, 16, 2, 886-897. (This paper receives the Best Paper Award (second runner-up) in IEEE Transactions on Automation Science and Engineering, 2020)
[27] Song, C.*, Liu, K., and Zhang, X. (2019), “A Generic Framework for Multisensor Degradation Modeling based on Supervised Classification and Failure Surface”, IISE Transactions, 51, 11, 1288-1302. (Feature article in ISE Magazine)
[28] Feng, T., Qian, X., Liu, K., and Huang, S. (2019), “Dynamic Inspection of Latent Variables in State-Space Systems”, IEEE Transactions on Automation Science and Engineering, 16, 3, 1232-1243.
[29] Kim, M.*, Song, C.*, and Liu, K. (2019), “A Generic Health Index Approach for Multisensor Degradation Modeling and Sensor Selection”, IEEE Transactions on Automation Science and Engineering, 16, 3, 1426-1437.
[30] Wang, D.*, Liu, K., and Zhang, X. (2019), “Spatiotemporal Thermal Field Modeling Using Partial Differential Equations with Time-Varying Parameters”, IEEE Transactions on Automation Science and Engineering, 17, 2, 646 - 657.
[31] Xian, X.*, Zhang, C., Bonk, S.*, and Liu, K. (2021), “Online Monitoring of Big Data Streams: A Rank-based Sampling Algorithm by Data Augmentation”, Journal of Quality Technology, 53, 2, 135-153.
[32] Wang, D.*, Liu, K., Zhang, X., and Wang, H. (2020), “Spatiotemporal Multitask Learning for 3D Dynamic Field Modeling”, IEEE Transactions on Automation Science and Engineering, 17, 2, 708-721. (This paper received the Best Student Paper Finalist award in the DAIS Section of Industrial and Systems Engineering Research Conference (ISERC), 2019)
[33] Xian, X.*, Ye, H.*, Wang, X., and Liu, K. (2021), “Spatiotemporal modeling and real-time prediction of origin-destination traffic demand”, Technometrics, 63, 77-89.
[34] Ye, H.*, Wang, X., and Liu, K. (2021), “Adaptive Preventive Maintenance for Flow Shop Scheduling with Resumable Processing”, IEEE Transactions on Automation Science and Engineering, 18, 106 - 113.
[35] Kim, M.*, and Liu, K.(2021), “A Bayesian Deep Learning Framework for Interval Estimation of Remaining Useful Life in Complex Systems by Incorporating General Degradation Characteristics”, IISE Transactions, 53, 326-340. (This paper received the Best Student Poster honorable mention award in Quality, Statistics, and Reliability Section of INFORMS, 2020; Feature article in ISE Magazine)
[36] Kim, M.*, Ou, E., Loh, P., Allen, T., Agasie, R., and Liu, K. (2020), “RNN-Based Online Anomaly Detection in Nuclear Reactors for Highly Imbalanced Datasets with Uncertainty”, Nuclear Engineering and Design, 364, 110699. (This paper received the Best Student Paper Finalist award (second place) in the Energy Systems section of Industrial and Systems Engineering Research Conference (ISERC), 2021)
[37] Wang, D.*, Zhang, X., and Liu, K. (2022), “A Spatiotemporal Prediction Approach for A 3D Thermal Field from Sensor Networks”, Journal of Quality Technology, 54, 215-235. (This paper received Best Student Paper Award in Data Mining Section of INFORMS, 2019)
[38] Wang, D.*, Zhang, X., and Liu, K. (2022), “A Generic Indirect Deep Learning Approach for Multisensor Degradation Modeling”, IEEE Transactions on Automation Science and Engineering, 19, 3, 1924 - 1940.
[39] Kim, M.*, Song, C.*, and Liu, K. (2022), “Individualized Degradation Modeling and Prognostics in a Heterogeneous Group via Incorporating Intrinsic Covariate Information”, IEEE Transactions on Automation Science and Engineering, 19, 1503 - 1516.
[40] Ma, Z., Wang, S., Kim, M.*, Liu, K., Chen, C., and Pan, W. (2021), “Transfer Learning of Memory Kernels in Coarse-grained Modeling”, Soft Matter, 17, 5864-5877.
[41] Song, C.*, Liu, K., and Zhang, X. (2021), “Collusion Detection and Ground Truth Inference in Crowdsourcing for Labeling Tasks”, Journal of Machine Learning Research, 22(190), 1−45. (This paper received the Best Paper award in the Quality, Statistics, and Reliability Section of INFORMS, 2019)
[42] Kim, M.*, Cheng, J. C., and Liu, K. (2021), “An Adaptive Sensor Selection Framework for Multisensor Prognostics”, Journal of Quality Technology, 53, 566-585.
[43] Ye, H.*, and Liu, K. (2022), “A generic online nonparametric monitoring and sampling strategy for high-dimensional heterogeneous processes”, IEEE Transactions on Automation Science and Engineering, 19, 3, 2079 - 2094. (This paper received the Best Student Paper Finalist award in the DAIS section of Industrial and Systems Engineering Research Conference (ISERC), 2021)
[44] Wang, D., Li, F., and Liu, K. (2023), “Modeling and Monitoring of a Multivariate Spatio-Temporal Network System”, IISE Transactions, 55, 4, 331-347.
[45] Song, C.*, Zheng, Z.*, and Liu, K. (2022), “Building Local Models for Flexible Degradation Modeling and Prognostics”, IEEE Transactions on Automation Science and Engineering, 19, 3483 - 3495.
[46] Ye, H.*, Xian, X.*, Cheng, J. C., Hable, B., Shannon, R. W., Elyaderani, M. K., and Liu, K. (2023), “Online Nonparametric Monitoring of Heterogeneous Data Streams with Partial Observations based on Thompson Sampling”, IISE Transactions, 55, 4, 392-404. (This paper received the Best Student Paper Finalist award in the QCRE Section of Industrial and Systems Engineering Research Conference (ISERC), 2020)
[47] Ou, E., Kim, M.*, Loh, P., Allen, T., Agasie, R., and Liu, K. (2022), “Automatic Recognition System for Document Digitization in Nuclear Power Plants”, Nuclear Engineering and Design, 398, 111975.
[48] Wang, D.*, Li, F., Liu, K., and Zhang, X. (2024), “Real-time Cyber-Physical Security Solution Leveraging an Integrated Learning-Based Approach”, ACM Transactions on Sensor Networks, 20, 2, 1-22.
[49] Ye, H.*, Zheng, Z.*, Cheng, J. C., Hable, B., and Liu, K. (2024), “Online monitoring of high-dimensional asynchronous and heterogeneous data streams for shifts in location and scale”, International Journal of Production Research, 62, 3, 720-736.
[50] Zheng, Z.*, Zhao, W., Hable, B., Gong, Y., Wang, J., Shannon, R. W., and Liu, K. (2024), “Transfer Learning-based Independent Component Analysis”, IEEE Transactions on Automation Science and Engineering, 21, 1, 783-798.
[51] Kim, M.*, Allen, T., and Liu, K. (2023), “Covariate Dependent Sparse Functional Data Analysis”, INFORMS Journal on Data Science, 2, 1, 81-98.
[52] Wang, D.*, and Liu, K. (2023), “An Integrated Deep Learning-Based Data Fusion and Degradation Modeling Method for Improving Prognostics”, IEEE Transactions on Automation Science and Engineering, in press.
[53] Fu, Y.*, Liu, K., and Zhu, W. (2023), “Instance Selection via Voronoi Neighbors for Binary Classification Tasks”, IEEE Transactions on Knowledge and Data Engineering, in press. (This paper received the Best Paper Finalist award in the DAIS Section of Industrial and Systems Engineering Research Conference (ISERC), 2023)
[54] Zheng, Z.*, Ye, H.*, and Liu, K. (2024), “Online Nonparametric Monitoring for Asynchronous Processes with Serial Correlation”, IISE Transactions, in press. 

Other publications
[1] Lin, Y., Liu, K., Byon, E., Qian, X., and Huang, S. (2015), “Domain-Knowledge Driven Cognitive Degradation Modeling of Alzheimer’s Disease”, The SIAM International Conference on Data Mining, 721-729.
[2] Liu, K. (2015), “Industrial data analytics courses: need, content and expectations – insights from 2015 ISERC panel discussion”, Industrial Engineer, 48, 4, 43-46. (Feature article in IIE Magazine)
[3] Liu, K., Klabjan, D., Shmoys, D., and Sokol, J. (2016), “Present and future of analytics education”, ORMS Today, 43, 5, 32-35. (Feature article in INFORMS Magazine)
*Students are advised by me