[J30] S. Yang, H. Xiong, Y. Zhang, Y. Ling, L. Wang, K. Xu, and Z. Sun*, 2022, OGM: Online gaussian graphical models on the fly, Applied Intelligence, 1-15.
[J29] M. M. Islam, Z. Sun*, R. Qin, W. Hu, H. Xiong, and K. Xu, 2022, Flexible energy load identification in intelligent manufacturing for demand response using a neural network integrated particle swarm optimization, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 0954406220933652.
[J28] J. Yang, Z. Sun*, W. Hu, L. Steinmeister, 2022, Joint control of manufacturing and onsite microgrid system via novel neural-network integrated reinforcement learning algorithms, Applied Energy, 315, 118982.
[J27] Y. Li, M. M. Karim, R. Qin*, Z. Sun, Z. Wang, and Z. Yin, 2021, Crash report data analysis for creating scenario-wise, spatio-temporal attention guidance to support computer vision-based perception of fatal crash risks, Accident Analysis & Prevention, 151, 105962.
[J26] S. Yang, J. Bian, H. Xiong, D. Hu, Z. Sun*, L. Wang, P. Zhu, and K. Xu, 2021, Generalising Combinatorial Discriminant Analysis through Conditioning Truncated Rayleigh Flow, Knowledge and Information System, 63(8), 2189-2208.
[J25] S. Yang, H. Xiong, K. Xu, L. Wang, J. Bian, and Z. Sun*, 2020, Improving Covariance-Regularized Discriminant Analysis for EHR-based Predictive Analytics of Diseases, Applied Intelligence, 51(1), 377-395.
[J24] J. Bian, S. Yang, H. Xiong, L. Wang, Y. Fu, Z. Sun, Z. Guo, J. Wang, 2020, CRLEDD: Regularized Causalities Learning for Early Detection of Diseases Using Electronic Health Record (EHR) Data, IEEE Transactions on Emerging Topics in Computational Intelligence, 5(4), 541-533.
[J23] Y. Li, R. Kesharwani, Z. Sun*, C. Dagli, R. Qin, M. Zhang, and D. Wang, 2020, Economic viability and environmental impact investigation for the biofuel supply chain using co-fermentation technology, Applied Energy, 259, 114235.
[J22] Y. Zhang, Y. Li, Z. Sun*, H. Xiong, R. Qin, and C. Li, 2019, Intelligent data-driven quality classification platform leveraging an integrated hyper learning framework towards cost effectiveness in manufacturing and service industry, Journal of Cleaner Production, 242, 118481.
[J21] Y. Zhang, Z. Sun*, R. Qin, and H. Xiong, 2021, Idle duration prediction for manufacturing system using a Gaussian mixture model integrated neural network for energy efficiency improvement, IEEE Transactions on Automation Science and Engineering, 18(1), 47-55.
[J20] M.M. Islam, X. Zhong, Z. Sun*, H. Xiong, and W. Hu, 2019, Real-time frequency regulation using aggregated Electric Vehicles in smart grid, Computer & Industrial Engineering, 134, 11-26.
[J19] R. Kesharwani, Z. Sun*, and C. Dagli, 2019, Moving second generation biofuel manufacturing forward: Investigating economic viability and environmental sustainability considering two strategies for supply chain restructuring, Applied Energy, 242, 1467-1496.
[J18] B. Nagarajan, Y. Li, Z. Sun*, and R Qin, 2019, A routing algorithm for inspecting grid transmission system using suspended robot: Enhancing cost-effective and energy efficient infrastructure maintenance, Journal of Cleaner Production, 219, 622-638.
[J17] M.M. Islam, and Z. Sun*, 2019, Onsite generation system sizing for manufacturing plant considering renewable sources towards sustainability, Sustainable Energy Technologies and Assessments, 32, 1-18.
[J16] H. Xiong*, W. Cheng, J. Bian, W. Hu, Z. Sun, and Z. Guo, 2018, DBSDA: Lowering the bound of misclassification rate for sparse linear discriminant analysis via model debiasing, IEEE Transactions on Neural Networks and Learning Systems, 30(3), 707-717.
[J15] Y. Zhang, M. M. Islam, Z. Sun*, S. Yang, C. Dagli, and H. Xiong, 2018, Optimal sizing and planning of onsite generation system for manufacturing in Critical Peaking Pricing demand response program, International Journal of Production Economics, 206, 261-267.
[J14] Z. Sun, F. Dababneh, and L. Li*, 2018, Joint energy, maintenance and throughput modeling for sustainable manufacturing systems, IEEE Transactions on Systems, Man, Cybernetics - Part A: Systems, 50(6), 2101-2112.
[J13] R. Kesharwani, Z. Sun*, and C. Dagli, 2018, Biofuel supply chain optimal design considering economic, environmental, and societal aspects towards sustainability, International Journal of Energy Research, 42(6), 2169-2198.
[J12] M. M. Islam, X. Zhong, H. Xiong, and Z. Sun*, 2018, Optimal scheduling of manufacturing and onsite generation systems in over-generation mitigation oriented electricity demand response program, Computers & Industrial Engineering, 115, 381-388.
[J11] Y. Yang, L. Li*, Y. Pan, and Z. Sun, 2017, Energy Consumption model of stereolithography-based additive manufacturing towards environmental sustainability, Journal of Industrial Ecology, 21, 168-178.
[J10] F. Dababneh, L. Li*, and Z. Sun, 2016, Peak power demand reduction for combined manufacturing and HVAC system considering heat transfer characteristics, International Journal of Production Economics, 177, 44-52.
[J9] Z. Sun, L. Li*, and F. Dababneh, 2016, Plant-level electricity demand response for combined manufacturing system and HVAC system, Journal of Cleaner Production, 135, 1650-1657.
[J8] L. Li*, Z. Sun, X. Yao, and D. Wang, 2016, Optimal production scheduling for energy efficiency improvement in biofuel feedstock preprocessing considering work-in-process particle separation, Energy, 96, 474-481.
[J7] Z. Sun, L. Li*, A. Bego, and F. Dababneh, 2015, Customer-side electricity load management for sustainable manufacturing systems utilizing combined heat and power generation system, International Journal of Production Economics, 165, 112-119.
[J6] Z. Sun, L. Li*, M. Fernandez, and J. Wang, 2014, Inventory control for peak electricity demand reduction of manufacturing systems considering the tradeoff between production loss and energy savings, Journal of Cleaner Production, 82, 84-93.
[J5] Z. Sun, and L. Li*, 2013, Opportunity estimation for real-time energy control of sustainable manufacturing systems, IEEE Transactions on Automation Science and Engineering, 10, 38-44.
[J4] Z. Sun, and L. Li*, 2013, Potential capability estimation for real time electricity demand response of sustainable manufacturing systems using Markov decision process, Journal of Cleaner Production, 65, 184-193.
[J3] L. Li*, and Z. Sun, 2013, Dynamic energy control for energy efficiency improvement of sustainable manufacturing systems using Markov decision process, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 43, 1195-1205.
[J2] M. Fernandez, L. Li*, and Z. Sun, 2013, “Just-for-Peak” buffer inventory for peak electricity demand reduction of manufacturing systems, International Journal of Production Economics, 146, 178-184.
[J1] A. Bego, L. Li*, and Z. Sun, 2013, Identification of reservation capacity in critical peak pricing electricity demand response program for sustainable manufacturing systems, International Journal of Energy Research, 38, 728-736.
CONFERENCE PUBLICATIONS
[C38] J. Zhu, Y. Cui, Z. Sun, Y. Dai, X. Wang, L. Liu, C. Luo, and L. Dai*, Adaptive Loss-aware Modulation for Multimedia Retrieval, accepted by 2024 IEEE International Conference on Data Mining, December 9-12, Abu Dhabi, UAE.
[C37] F. Huang*, Y. Deng, C. Zhang, M. Guo, K. Zhan, S. Sun, J. Jiang, Z. Sun, and X. Wu, KOSA: KO enhanced salary analytics based on knowledge graph and LLM capabilities, in Proceedings of 2023 IEEE International Conference on Data Mining Workshops (ICDMW), 499-505, December 1-4, 2023, Shanghai, China.
[C36] Y. Li, H. Xiong, L. Kong, Z. Sun, H. Chen, S. Wang, and D. Yin, 2023, MPGraf: a Modular and Pre-trained Graphformer for Learning to Rank at Web-scale, in Proceedings of 2023 IEEE International Conference on Data Mining (ICDM), 339-348, December 1-4, 2023, Shanghai, China. Best Student Paper Award
[C35] M. Guo, F. Wu, J. Jiang, X. Yan, G. Chen, W. Li, Y. Zhao, and Z. Sun, 2023, Investigations on Scientific Literature Meta Information Extraction Using Large Language Models, in Proceedings of 2023 IEEE International Conference on Knowledge Graph (ICKG), 249-254, December 1-2, 2023, Shanghai, China.
[C34] Y. Li, H. Xiong, L. Kong, S. Wang, Z. Sun, H. Chen, G. Chen, and D. Yin, 2023, Ltrgcn: Large-scale graph convolutional networks-based learning to rank for web search, in Proceedings of 2023 Joint European Conference on Machine Learning and Knowledge Discovery in Database (ECML PKDD), 635-651, September 18-22, 2023, Turin, Italy.
[C33] X. Zhou, J. Zhao, L. Yun, Z. Sun, and L. Li*, 2020, Demand response for sustainable manufacturing systems considering buffer content utilization, in Proceedings of 2020 ASME Manufacturing Science and Engineering Conference (MSEC), September 3, 2020, Virtual Event.
[C32] Y. Li, Z. Sun, K. Xu, and R. Qin*, 2020, A Two-Layer routing algorithm for unmanned aerial vehicle in transmission line inspection. in Proceedings of 2020 International Annual Conference of American Society for Engineering Management, October 28-30, 2020, Virtual Event. Best Paper Award.
[C31] M.M. Islam, C. Dagli*, and Z. Sun, 2019 A model to estimate the lifetime of BESS for the prosumer community of manufacturers with OGS, Procedia Computer Science, 168, 186-194, Complex Adaptive Systems Conference, November 13-15, 2019, Malvern, PA, U.S.
[C30] M.M., Islam, Z. Sun*, and W. Hu, 2019, A framework of integrating manufacturing plants in smart grid operation: manufacturing flexible load identification, in proceedings of the 25th International Conference of Production Research, August 10-August 15, Chicago, IL, U.S.
[C29] Y. Zhang, W. Hu, and Z. Sun*, 2019, Joint manufacturing and onsite microgrid system control using Markov Decision Process and neural network integrated reinforcement learning, in proceedings of the 25th International Conference of Production Research, August 10-August 15, Chicago, IL, U.S.
[C28] S. Yang, J. Bian, Z. Sun*, L. Wang, H. Zhu, H. Xiong, and Y. Li, 2018, Early detection of disease using electronic health records and fisher's Wishart discriminant analysis, Procedia Computer Science, 140, 393-402. Complex Adaptive Systems Conference, November 5-7, 2018, Chicago, IL, U.S.
[C27] Y. Li, Z. Sun*, and R. Qin, 2018, Routing algorithm and cost analysis for using hydrogen fuel cell powered unmanned aerial vehicle in high voltage transmission line inspection, in Proceedings of 2018 International Annual Conference of American Society for Engineering Management, October 17-20, 2018, Coeur d’Alene, ID, U.S.
[C26] J.C. Morgan, M.M. Calvin, Z. Sun, and R. Qin*, 2018, Energy sharing community as a decentralized complex adaptive system of systems, in Proceedings of 2018 Institute for Industrial and Systems Engineers Annual Conference, May 19-22, Orlando, FL, U.S.
[C25] M.M. Islam, Z. Sun*, and R. Qin, 2018, Simulation-based investigation on economic feasibility of frequency regulation using aggregated electric vehicles in smart grid, in Proceedings of 2018 Institute for Industrial and Systems Engineering Annual Conference, May 19-22, Orlando, FL, U.S.
[C24] X. Zhong, M.M. Islam, H. Xiong, and Z. Sun*, 2017, Design the capacity of onsite generation system with renewable sources for manufacturing plant, Procedia Computer Science, 114, 433-440. Complex Adaptive Systems Conference, October 30-November 1, 2017, Chicago, IL, U.S.
[C23] M.M. Islam, Z. Sun*, and C. Dagli, 2017, Reward/Penalty design in demand response for mitigating overgeneration considering the benefits from both manufacturers and utility company, Procedia Computer Science, 114, 425-432. Complex Adaptive Systems Conference, October 30-November 1, 2017, Chicago, IL, U.S.
[C22] X. Zhong, M. M. Islam, N. Heffernan, H. Xiong, Z. Sun*, 2017, Learning curve analysis using intensive longitudinal and cluster-correlated data, Procedia Computer Science, 114, 250-257. Complex Adaptive Systems Conference, October 30-November 1, 2017, Chicago, IL, U.S.
[C21] M.M. Islam, Z. Sun*, and C. Dagli, 2017, A general algorithm for assessing product architecture performance considering architecture extension in cyber manufacturing, Procedia Computer Science, 114, 384-391. Complex Adaptive Systems Conference, October 30-November 1, 2017, Chicago, IL, U.S.
[C20] B. Nagarajan, R. Qin, Z. Sun*, and M.M. Islam 2017, Cost analysis for high voltage transmission line inspection using robot, in Proceedings of 2017 International Annual Conference of American Society for Engineering Management, October 18-21, 2017, Huntsville, AB, U.S.
[C19] M.M. Islam, Z. Sun*, and C. Dagli, 2017, Simulation-based investigations on electricity demand response for manufacturing systems to mitigate overgeneration due to high penetration of renewable sources, in proceedings of the 24th International Conference of Production Research, July 30-August 3, Poznan, Poland
[C18] F. Dababneh, R. Shah, L. Li*, and Z. Sun, 2017, Sensitivity analysis of joint energy and maintenance planning considering production throughput requirements, in Proceedings of ASME 2017 Manufacturing Science and Engineering Conference (MSEC), June 4-8, 2017, Los Angeles, CA, U.S.
[C17] R. Kesharwani, X. Song, Y. Yang, Z. Sun*, M. Zhang, and C. Dagli, 2017, Investigation of relationship between sugar yield and particle size in biofuel manufacturing, in Proceedings of ASME 2017 Manufacturing Science and Engineering Conference (MSEC), June 4-8, 2017, Los Angeles, CA, U.S.
[C16] R. Kesharwani, M. M. Islam, X. Song, Z. Sun*, M. Zhang, and C. Dagli, 2017, A case study investigating the environmental impact of pelleting in cellulosic biofuel manufacturing, in Proceedings of ASME 2017 Manufacturing Science and Engineering Conference (MSEC), June 4-8, 2017, Los Angeles, CA, U.S.
[C15] R. Li, and Z. Sun*, 2017, A data-driven approach to detect mechanical faults in wind turbine gearbox, in Proceedings of ASME 2017 Manufacturing Science and Engineering Conference (MSEC), June 4-8, 2017, Los Angeles, CA, U.S.
[C14] R. Kesharwani, C. Dagli, Z. Sun*, 2016, Application of neural network in shop floor quality control in a make to order business, Procedia Computer Science, 95, 209-216.
[C13] M. M. Islam, Z. Sun*, and X. Yao, 2016, Simulation-based investigation for the application of microgrid with renewable sources in manufacturing systems towards sustainability, in Proceedings of 2016 Annual Conference of the American Society for Engineering Management (MSEC), October 26-29, 2016, Charlotte, NC, U.S.
[C12] J. Y. Joo*, S. Raghavan1, and Z. Sun, 2016, Integration of sustainable manufacturing systems into smart grids with high penetration of renewable energy resources, in Proceedings of 2016 IEEE Annual Green Technologies Conference, April 6-8, 2016, Kansas City, MO, U.S.
[C11] X. Yao, Z. Sun*, D. Wei, and L. Wang, 2016, Joint maintenance and energy management in manufacturing systems: prospect discussion, challenge analysis, and a case study, in Proceedings of ASME 2016 Manufacturing Science and Engineering Conference (MSEC), June 27-July 1, 2016, Blacksburg, VA, U.S.
[C10] Z. Sun*, D. Wei, L. Wang, and L. Li, 2015, Data driven production runtime energy control of manufacturing systems towards sustainability, in Proceedings of 2015 IEEE Conference on Automation Science and Engineering (CASE), Gothenburg, Sweden.
[C9] Z. Sun*, D. Wei, L. Wang, and L. Li, 2015, Energy-integrated production scheduling in industrial energy management system, in Proceedings of 2015 IEEE Conference on Automation Science and Engineering (CASE), Gothenburg, Sweden.
[C8] F. Dababneh, M. Atanasov, Z. Sun, and L. Li*, 2015, Simulation-based electricity demand response for combined manufacturing and HVAC system towards sustainability, in Proceedings of ASME 2015 Manufacturing Science and Engineering Conference (MSEC), June 8-12, 2015, Charlotte, NC, U.S.
[C7] X. Yao, Z. Sun, and L. Li*, 2015, Joint maintenance and energy management of sustainable manufacturing systems, in Proceedings of ASME 2015 Manufacturing Science and Engineering Conference (MSEC), June 8-12, 2015, Charlotte, NC, U.S.
[C6] L. Cuyler, Z. Sun, and L. Li*, 2014, Simulation-based optimization of electricity demand response for sustainable manufacturing systems, in Proceedings of ASME 2014 Manufacturing Science and Engineering Conference (MSEC), June 9-13, 2014, Detroit, MI, U.S.
[C5] Z. Sun, D. Wang, L. Li*, and M. Zhang, 2014, Relationship investigation between energy consumption and parameters in size reduction and pelleting processes of biofuel manufacturing, in Proceedings of ASME 2014 Manufacturing Science and Engineering Conference (MSEC), June 9-13, 2014, Detroit, MI, U.S.
[C4] L. Li*, Z. Sun, X. Xu, and K, Zhang, 2013, Multi-zone proportional hazard model for a multi-stage degradation process, in Proceedings of ASME 2013 Manufacturing Science and Engineering Conference (MSEC), June 10-14, 2013, Madison, WI, U.S.
[C3] L. Li*, Z. Sun, H. Yang, and F. Gu, 2012, Simulation-based energy efficiency improvement for sustainable manufacturing systems, in Proceedings of ASME 2012 Manufacturing Science and Engineering Conference (MSEC), June 4-8, 2012, South Bend, IN, U.S.
[C2] L. Li*, Z. Sun, and Z. Tang, 2012, Real time electricity demand response for sustainable manufacturing systems: Challenges and a case study, in Proceedings of 2012 IEEE Conference on Automation Science and Engineering (CASE), Seoul, Korea.
[C1] Z. Sun, S. Biller, F. Gu, and L. Li*, 2011, Energy consumption reduction for sustainable manufacturing systems considering machines with multiple-power states, in Proceedings of ASME 2011 Manufacturing Science and Engineering Conference (MSEC), June 13-17, 2011, Corvallis, OR, U.S.