{"id":64,"date":"2024-02-23T15:11:48","date_gmt":"2024-02-23T15:11:48","guid":{"rendered":"https:\/\/faculty.eng.ufl.edu\/template-mercury\/?page_id=64"},"modified":"2026-03-24T09:50:10","modified_gmt":"2026-03-24T14:50:10","slug":"publications","status":"publish","type":"page","link":"https:\/\/faculty.eng.ufl.edu\/jia-peter-liu\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"\n<section class=\"title-block w-100\"><div class=\"container-fluid page-title-container\"><div class=\"title-wrapper\"><h1 class=\"font-heading\">Publications<\/h1><hr \/><p>The journal and conference publications<\/p><\/div><\/div><\/section>\n\n\n\n<div style=\"height:0px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<section class=\"fullwidth-text-block\"><div class=\"container px-0\"><div class=\"row align-items-start\"><div class=\"col-12\">\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\">\n<h2 class=\"wp-block-heading\">Journal Articles<\/h2>\n\n\n\n<ul class=\"wp-block-list has-light-gray-background-color has-background\">\n<li>Qasaimeh, Q*., Li, H., Hamasha, S., <strong>Liu, J.<\/strong> (2025), \u201cA Machine Learning Framework with Shapley&#8217;s Additive Explanations to Assess Solder Joint Reliability for Electronic Packaging\u201d, <em>Journal of Electronic Materials<\/em>, 54, 7586\u20137608, DOI:10.1007\/s11664-025-12101-4.<\/li>\n\n\n\n<li>Hossain, M., Silva, D., Vinel, A., West, B., Shamsaei, N., <strong>Liu, J.<\/strong> (2025), \u201cInvestigation of Inconel 718 powder flowability for laser beam powder bed fusion using physics-informed machine learning framework\u201d, <em>Powder Metallurgy<\/em>, DOI:10.1177\/00325899251339973.<\/li>\n\n\n\n<li>Mahmood, S., Baugh, L., Lee, S., Ahmad, N., Silva, D., Vinel, A., <strong>Liu, J.<\/strong>, Shao, S., Shamsaei, N., Jackson, R., Schulze, K. (2025), \u201cA comparative analysis of non-destructive surface topography measurement techniques for additively manufactured metal parts\u201d, <em>Additive Manufacturing<\/em>, 105, 104791, DOI: 10.1016\/j.addma.2025.104791.<\/li>\n\n\n\n<li>Ahmad, N., Irfan, S.*, Maleki, E., Lee, S., <strong>Liu, J.<\/strong>, Shao, S., Shamsaei, S. (2025), \u201cDetermining critical surface features affecting fatigue behavior of additively manufactured Ti-6Al-4V\u201d, <em>International Journal of Fatigue<\/em>, 197, 108956, DOI: 10.1016\/j.ijfatigue.2025.108956.<\/li>\n\n\n\n<li>Qasaimeh, Q*., <strong>Liu, J.<\/strong>, Qasaimeh, A., Evans, J., Hamasha, S. (2025), \u201cInterpretable data-driven framework for life prediction of homogenous lead-free solder joints in ball grid array packages\u201d,<em> Journal of Intelligent Manufacturing,<\/em> DOI: 10.1007\/s10845-025-02564-x.<\/li>\n\n\n\n<li>Nikfar, M., Irfan, S.*, Baugh, L., Mahood, S., Ahmad, N., <strong>Liu., J.<\/strong>, et al. (2025), \u201cOn extreme value theory-based estimation of surface quality for metal additive manufacturing\u201d, <em>Progress in Additive Manufacturing, <\/em>DOI:10.1007\/s40964-025-00998-6.<\/li>\n\n\n\n<li>Haynes, K., Harris, G., Schall, M., <strong>Liu, J.<\/strong>, Davis, J. (2024), \u201cGauging the Technology Acceptance of Manufacturing Employees: A New Measure for Pre-Implementation\u201d, <em>Sustainability<\/em>, 16(12), 4969.<\/li>\n\n\n\n<li>Li, A.*, Poudel, A., Shao, S., Shamsaei, N., <strong>Liu, J.<\/strong> (2024), \u201cNondestructive Fatigue Life Prediction for Additively Manufactured Metal Parts through a Multimodal Transfer Learning Framework\u201d, <em>IISE Transactions,<\/em> 1-16.<\/li>\n\n\n\n<li><strong>Liu, J.,<\/strong> Ye, J.*, Silva, D., Vinel, A., Shamsaei, N., Shao, S. (2023), \u201cA Review of Machine Learning Techniques for Process and Performance Optimization in Laser Beam Powder Bed Fusion Additive Manufacturing\u201d, <em>Journal of Intelligent Manufacturing,<\/em> 34 (8), 3249-3275.<\/li>\n\n\n\n<li>Ye, J.*, Poudel, A., <strong>Liu, J.<\/strong>, Vinel, A., Silva, D., Shao, S., Shamsaei, N., (2023), \u201cMachine Learning Augmented X-Ray Computed Tomography Features for Volumetric Defect Classification in Laser Beam Powder Bed Fusion\u201d, <em>International Journal of Advanced Manufacturing Technology, <\/em>126 (7), 3093-3107.<\/li>\n\n\n\n<li>Gu, Z., Zhu, R., Shen, T., Lin, D., Liu, H., Liu, Y., Liu, X.,<strong> Liu, J.<\/strong>, Zhuang, S., Gu, F. (2023), \u201cAutonomous Nanorobots with Powerful Thrust under Dry Solid-contact Conditions by Photothermal Shock\u201d,<em> Nature Communications,<\/em> 14 (1), 7663.<\/li>\n\n\n\n<li>Gao, T.*, Li, A.*, Zhang, X., Harris, G., <strong>Liu, J.<\/strong> (2023), \u201cA Data-driven Process-quality-property Analytical Framework for Conductive Composites in Additive Manufacturing\u201d, <em>Manufacturing Letters, <\/em>35, 626-635.<\/li>\n\n\n\n<li>Jayswal, A., <strong>Liu, J.<\/strong>, Harris, G., Mailen, R., Adanur, S., (2023), \u201cCreep Behavior of 3D Printed Polymer Composites\u201d, <em>Polymer Engineering and Science, <\/em>63 (11), 3809-3818.<\/li>\n\n\n\n<li>Jayswal, A., <strong>Liu, J.<\/strong>, Harris, G., Adanur, S. (2023), \u201cThermo-mechanical Properties of Composite Filaments for 3D Printing of Fabrics\u201d, <em>Journal of Thermoplastic Composite Materials, <\/em>36 (12), 4800-4825.<\/li>\n\n\n\n<li>Jayswal, A., Mailen, R.,<strong> Liu, J.<\/strong>, Harris, G., Siwakoti, M., Adanur, S. (2023), \u201cThermo-mechanical Behavior of 3D Printed Fabric Structures\u201d,<em> Polymer Engineering and Science<\/em>, 63, 1725-1736.<\/li>\n\n\n\n<li><strong>Liu, J.<\/strong>, Ye, J.*, Momin, F., Zhang, X., Li, A*. (2022), \u201cNonparametric Bayesian framework for material and process optimization with nanocomposite fused filament fabrication\u201d, <em>Additive Manufacturing,<\/em> 54, 102765.<\/li>\n\n\n\n<li>Poudel, A., Yasin, M., Ye, J.*, <strong>Liu, J.<\/strong>, Vinel, A., Shao, S., Shamsaei, N. (2022), \u201cFeature-based Volumetric Defect Classification in Metal Additive Manufacturing\u201d, <em>Nature Communications,<\/em> 13 (1), 6369.<\/li>\n\n\n\n<li>Li, A.*, Baig, S., <strong>Liu, J.<\/strong>, Shao, S., Shamsaei, N. (2022), \u201cDefect Criticality Analysis on Fatigue Life of L-PBF 17-4 PH Stainless Steel via Machine Learning\u201d, <em>International Journal of Fatigue,<\/em> 163, 107018.<\/li>\n\n\n\n<li>Osho, J., Hyre, A., Pantelidakis, M., Ledford, A., Harris, G., <strong>Liu, J.<\/strong>, Mykoniatis, K. (2022), \u201cFour Rs Framework for the Development of a Digital Twin: The Implementation of Representation with an FDM Manufacturing Machine\u201d, <em>Journal of Manufacturing Systems, <\/em>63, 370-380.<\/li>\n\n\n\n<li>Pantelidakis, M., Mykoniatis, K., <strong>Liu, J.<\/strong>, Harris, G. (2022), \u201cA Digital Twin Ecosystem for Additive Manufacturing Using a Real-time Development Platform\u201d, <em>International Journal of Advanced Manufacturing Technology,<\/em> 120 (9),&nbsp;6547-6563.<\/li>\n\n\n\n<li>Hyre, A., Harris, G., Osho, J., Pantelidakis, M., Ledford, A., Mykoniatis, K., <strong>Liu, J.<\/strong> (2022), \u201cDigital Twins: Representation, Replication, Reality, and Relational (4Rs)\u201d, <em>Manufacturing Letters,<\/em> 31, 20-23.<\/li>\n\n\n\n<li>Ali, H., Ahmed, A., Matus, C., <strong>Liu, J.<\/strong> (2022), \u201cMitigating Urinary Incontinence Condition Using Machine Learning\u201d, <em>BMC Medical Informatics and Decision Making,<\/em> 22 (1), 243.<\/li>\n\n\n\n<li>Gao, Y., Cao, Z., <strong>Liu, J.<\/strong>, Zhang, J. (2021), \u201cA Novel Dynamic Brain Network in Arousal for Brain States and Emotion Analysis\u201d, <em>Mathematical Biosciences and Engineering, <\/em>18 (6), 7440-7463.<\/li>\n\n\n\n<li>Gao, Y., Gao, B., Chen, Q., <strong>Liu, J.<\/strong>, Zhang, Y. (2020), \u201cDeep Convolutional Neural Networks based Epileptic Electroencephalogram (EEG) Signal Classification\u201d, <em>Frontiers in Neurology,<\/em> 11, 375.<\/li>\n\n\n\n<li><strong>Liu, J.<\/strong>, Zheng, J., Rao. P., Kong, Z. (2020), \u201cMachine Learning Driven In-situ Process Monitoring with Vibration Frequency Spectra for Chemical Mechanical Planarization\u201d,<em> International Journal of Advanced Manufacturing Technology, <\/em>111 (7), 1873-1888.<\/li>\n\n\n\n<li><strong>Liu, J.<\/strong>, Liu, C., Bai, Y., Rao. P., Williams, C., Kong, Z. (2019), \u201cLayer-wise Spatial Modeling of Porosity in Additive Manufacturing\u201d, <em>IISE Transactions,<\/em> 51(2), 109-123. <strong>Featured by ISE Magazine, Vol. 51, No. 1, January 2019&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<\/strong><\/li>\n\n\n\n<li><strong>Liu, J.<\/strong>, Jin, R., Kong, Z. (2018), \u201cWafer Quality Monitoring using Spatial Dirichlet Process based Mixed-effect Profile Modeling Scheme\u201d, <em>Journal of Manufacturing Systems,<\/em> 48, 21-32.<\/li>\n\n\n\n<li><strong>Liu, J.<\/strong>, Beyca, O., Rao, P., Kong, Z., Bukkapatnam, S. (2016), \u201cDirichlet Process Gaussian Mixture Models for Real-Time Monitoring and Their Application to Chemical Mechanical Planarization\u201d, <em>IEEE Transactions on Automation Science and Engineering,<\/em> 14 (1), 208-221.<\/li>\n\n\n\n<li>Rao, P., <strong>Liu, J.<\/strong>, Roberson, D., Kong, Z. (2015), \u201cOnline Real-time Quality Monitoring in Additive Manufacturing Processes Using Heterogeneous Sensors\u201d, <em>ASME Trans Journal of Manufacturing Science and Engineering,<\/em> 137 (6), 1007-1 &#8211; 1007-12.<\/li>\n\n\n\n<li>Yu, Z., Wang, L., <strong>Liu, J<\/strong>. (2013), \u201cA General Steel Hardenability Calculation Method\u201d, <em>Advanced Materials Research,<\/em> 816, 140-143.<\/li>\n<\/ul>\n\n\n\n<div style=\"height:90px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Conference Proceedings<\/h2>\n\n\n\n<ul class=\"wp-block-list has-light-gray-background-color has-background has-small-font-size\">\n<li>Qasaimeh, Q.*, Li, H., Hamasha, S., Evans, J., <strong>Liu, J.<\/strong> (2024), \u201cInterpretable Machine Learning Models Can Outperform Statistical Models in Solder Joint Reliability\u201d, <em>23rd IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems,<\/em> Aurora, CO, USA, May 28-31, 2024.<\/li>\n\n\n\n<li><strong>Liu, J., <\/strong>Qasaimeh, Q.* (2024), \u201cPhysics-Informed Machine Learning for Solder Design and Reliability Prediction for Electronics\u201d, <em>Proceedings of 2024 Pan Pacific Strategic Electronics Symposium (Pan Pacific)<\/em>, Kona, Big Island, HI, USA, Jan 29 &#8211; Feb 1, 2024.<\/li>\n\n\n\n<li>Pantelidakis, M., Katsigiannis, M., Mykoniatis, K., Purdy, G., <strong>Liu, J.<\/strong> (2023), \u201cCondition monitoring for Overall Equipment Effectiveness using Internet of Things, Edge Computing, and Extended Reality\u201d, <em>IEEE Conference Proceedings of the 2nd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME 2023)<\/em>, Tenerife-canary Islands, Spain, Jul 19-20, 2023.<\/li>\n\n\n\n<li>Gao, T.*, Li, A., Zhang, X., Harris, G., <strong>Liu, J.<\/strong> (2023), \u201cA Data-driven Process-Quality-Property Analytical Framework for Conductive Composites in Additive Manufacturing\u201d, <em>SME NAMRC 51,<\/em> New Brunswick, NJ, Jun 12-16, 2023.<\/li>\n\n\n\n<li>Qasaimeh, Q.*, <strong>Liu, J.<\/strong>, Qasaimeh, A., Evans, J., Hamasha, S. (2023), \u201cPredicting the Fatigue Life of the Solder Joints in Electronic Assemblies using Physics-informed Data-driven Methodology\u201d, <em>22nd IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems,<\/em> Orlando, FL, May 30 &#8211; Jun 2, 2023.<\/li>\n\n\n\n<li>Li, A.*, <strong>Liu, J.<\/strong>, Shao, S., Shamsaei, N. (2022), \u201cDefects Classification via Hierarchical Graph Convolutional Network in L-PBF Additive Manufacturing\u201d, <em>Proceedings of the 2022 Annual International Solid Freeform Fabrication Symposium<\/em>, Austin, TX, Jul 22-27, 2022.&nbsp;<\/li>\n\n\n\n<li>Osho, J., Hyre, A., Pantelidakis, M., Ledford, A., Harris, G., <strong>Liu, J.<\/strong>, Mykoniatis, K. (2022) \u201cFour Rs Framework for the Development of a Digital Twin: The Implementation of Representation with an FDM Manufacturing Machine\u201d, <em>SME NAMRC 50<\/em>, West Lafayette, IN, Jun 27-Jul 1, 2022.<\/li>\n\n\n\n<li>Ye, J.*, Yasin, M., <strong>Liu, J.<\/strong>, Vinel, A., Silva, D., Shamsaei, N., Shao, S. (2021), \u201cBayesian Process Optimization for Additively Manufactured Nitinol\u201d, <em>Proceedings of the 2021 Annual International Solid Freeform Fabrication Symposium<\/em>, Virtual, Aug 2-4, 2021.<\/li>\n\n\n\n<li>Abolmaali, S., Vinel, A., Fox, J., <strong>Liu, J.,<\/strong> Silva, D., Shamsaei, N. (2021), \u201cLocation and Orientation Dependency in Surface Roughness of Nickel Super Alloy 625 Parts: Statistical and Distributional Analysis\u201d, <em>Proceedings of the 2021 Annual International Solid Freeform Fabrication Symposium<\/em>, Virtual, Aug 2-4, 2021.<\/li>\n\n\n\n<li>Hossain, M.*, Silva, D., Vinel, A., <strong>Liu, J.<\/strong>, Shamsaei, N. (2021), \u201cPowder Features Affecting Structural and Mechanical Properties of Additively Manufactured Inconel 718: A Machine Learning Analysis\u201d, <em>Proceedings of the 2021 Annual International Solid Freeform Fabrication Symposium<\/em>, Virtual, Aug 2-4, 2021.<\/li>\n\n\n\n<li>Rao, P., <strong>Liu, J.<\/strong>, Roberson, D., Kong, Z., Williams, C. (2015), \u201cSensor-based Online Process Fault Detection in Additive Manufacturing\u201d, <em>Proceedings of the ASME 2015 10th International Manufacturing Science and Engineering Conference<\/em>, Charlotte, NC, Jun 8-12, 2015.<\/li>\n\n\n\n<li><strong>Liu, J.<\/strong>, Sun, Y. (2013), \u201cMultivariate Statistical Process Monitoring Scheme with PLS and SVDD\u201d, <em>Proceedings of 20th International Conference on Industrial Engineering and Engineering Management<\/em>, Baotou, China, Aug 17-18, 2013.<\/li>\n\n\n\n<li><strong>Liu, J.<\/strong>, Sun, Y., Xu, H., Yu, Z. (2013), \u201cPCA-based Weighted Similarity Calculation Algorithm for Steel Materials Matching\u201d, <em>Proceedings of 32nd Chinese Control Conference<\/em>, Xi\u2019an, China, Jul 26-28, 2013.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div><\/div><\/div><\/section>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":1281,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"inline_featured_image":false,"featured_post":"","footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-64","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/faculty.eng.ufl.edu\/jia-peter-liu\/wp-json\/wp\/v2\/pages\/64","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/faculty.eng.ufl.edu\/jia-peter-liu\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/faculty.eng.ufl.edu\/jia-peter-liu\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/faculty.eng.ufl.edu\/jia-peter-liu\/wp-json\/wp\/v2\/users\/1281"}],"replies":[{"embeddable":true,"href":"https:\/\/faculty.eng.ufl.edu\/jia-peter-liu\/wp-json\/wp\/v2\/comments?post=64"}],"version-history":[{"count":7,"href":"https:\/\/faculty.eng.ufl.edu\/jia-peter-liu\/wp-json\/wp\/v2\/pages\/64\/revisions"}],"predecessor-version":[{"id":44243,"href":"https:\/\/faculty.eng.ufl.edu\/jia-peter-liu\/wp-json\/wp\/v2\/pages\/64\/revisions\/44243"}],"wp:attachment":[{"href":"https:\/\/faculty.eng.ufl.edu\/jia-peter-liu\/wp-json\/wp\/v2\/media?parent=64"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}