
隆建 副教授、博士生导师
地址:华东理工大学徐汇校区实验19楼1406室
电话:021-64253720
邮箱:longjian@ecust.edu.cn
【个人简介】
2019.09-至今 | 华东理工大学,信息科学与工程学院,副教授 |
2015.12-2019.08 | 华东理工大学,信息科学与工程学院,讲师 |
2013.09-2015.11 | 华东理工大学,师资博士后 |
2012.07-2013.08 | 石油化工科学研究院,工程师 |
2007.09-2012.06 | 华东理工大学,化工学院,博士 |
2003.09-2007.06 | 华东理工大学,化工学院,学士 |
【所获荣誉】
1. 中国专利优秀奖
2. 上海市科技进步一等奖
3. 上海市技术发明一等奖
4. 中国人工智能学会优秀科技成果奖
【学术兼职】
1. IEEE电气和电子工程师协会会员、中国自动化学会学员、中国过程系统工程学会会员
2. Expert Syst. Appl.、IEEE TII、IEEE TNSE、Fuel、JPC、CES、IECR等信息、能源、化工、控制领域顶级/著名期刊审稿人
3. 国基金青年/面上项目评审专家、受邀Process期刊客座编辑
【研究方向】
1. 机器学习与人工智能及其应用
2. 工业过程系统工程及智能制造
3. 医学图像处理与分析、医疗大数据
4. 新能源生产过程多尺度智能混合建模与优化
5. 鲁棒优化、博弈优化及其在工业生产、公共管理智能决策中应用
【承担项目】
1. 国家自然科学基金委员会,面上项目,新型变径流化床油转化催化反应过程多尺度耦合建模与多模态鲁棒优化,在研,主持;
2. 科技部重点研发课题,石油基乙烯流程工艺仿真共性技术平台,在研,参与;
3. 国家自然科学基金委员会,面上项目,油品近红外在线多模态智能检测和表征,结题,主持;
4. 国家自然科学基金委员会,青年项目:基于预设重构并融合密度泛函理论和单位键指标-二次指数势法的催化裂化分子尺度动力学研究,结题,主持;
5. 国家自然科学基金委员会,国际(地区)合作与交流项目,炼油装置短期最优操作运行研究,结题,技术骨干;
6. 国家自然科学基金委员会,重大项目,炼油生产过程全局优化运行的基础理论与关键技术--课题1炼油生产过程全局优化运行的集成建模理论与技术,结题,技术骨干;
7. 教育部,中央高校基本科研业务费专项资金-重点科研基地创新基金项目,原油快速评价研究,结题,主持。
8. 企业项目数项,如:工业催化裂化装置智能运行优化、渣油加氢催化剂剩余寿命预测、航空汽油生产方案研发、大型炼厂虚拟制造系统,等。
【主要成果】
研发了生产过程多尺度特性表征与智能建模方法、多尺度多目标资源优化决策方法,形成了知识产权自主可控的智能制造系统,实现了大型石化企业核心过程智能协同优化。在国内外学术期刊,如Chem. Eng. Sci.、Appl. Energy、Energy、Fuel、Comput. Chem. Eng.、Chin. J. Chem. Eng.、Expert Syst. Appl.、Adv. Eng. Inf.、Comput. Ind. Eng.等化工、能源、信息、人工智能、管理领域顶级/著名期刊,发表了学术论文70余篇,其中SCI论文60余篇。公开和申请国家发明专利50余项,已授权15项;申请国际PCT专利5项,登记计算机软著作权50余项。
【近年来发表的代表性论文】
1.Jian Long, Siyu Jiang, Luyao Wang, Jiazi Zhai, Feng Zhang*, Liang Zhao*. A Feature Optimized Attention Transformer with Kinetic Information Capture and Weighted Robust Z-score for Industrial NOx Emission Forecasting. Energy, 2025, 326:136276.
2. Renchu He, Rui Bian, Junjie Hua, Liang Zhao, Feng Xu*, and Jian Long*. Multi-objective optimization of gasoline blending scheduling via NSGA-II algorithm with composite operators considering oil. Expert Systems with Applications. 2025, 280:127426.
3. Xiangming Chen, Kai Luo, Cheng Huang, Jiahao Gong, Jian Long*, Wenze Guo*. Hybrid Modeling of Catalytic Cracking Processes Based on Seventeen-Lump Kinetic Model and Light Gradient Boosting Machine[J]. Energy & Fuels, 2025, 39 (14): 6942-6956.(期刊封面论文)
4. Zhi Li, Yuchong Xia, Jian Long*, Chensheng Liu and Longfei Zhang. Multi-scale feature fused stacked autoencoder and its application for soft sensor modeling[J]. Chin. J. Chem. Eng., Available online 9 March 2025.
5. Liang Zhao, Jiyun Rong, Guofu Ma, Jian Long*, Chen Liang. Multi-stage stochastic programming for integrated optimization of ethylene production processes and utility systems under uncertainty[J]. Energy, 2025, 320: 135295.
6. Zhe Wang, Renchu He*, Jian Long*. Systematic data-driven modelling framework for nonlinear distillation processes incorporating K-means data interval clustering, MIC and integrated learning algorithm[J]. Chin. J. Chem. Eng., Available online 8 March 2025.
7. Chen Fan, Xindong Wang, Jian Long*. Kinetic modeling and multi-objective optimization of an industrial hydrocracking process with an improved SPEA2-PE algorithm[J]. Chin. J. Chem. Eng., 2025, 80:130-146.
8. Guihua Hu, Mimi Chen, Jian Long*. Novel reduced-order framework combining proper orthogonal decomposition and multi-parallel Gaussian process regression: multi-physics prediction of ethylene cracking furnaces[J]. Chemical Engineering Science, 2025, 305: 121170.
9. Jian Long, Jiawei Zhu, Ning Wang, Jiazi Zhai, Tiantian Xu, Cheng Liang*, Liang Zhao*. Data-driven robust optimization for refinery operation in material-energy coupling systems under uncertainty[J]. Expert Systems with Applications, 2025, 267: 126184.
10. Renchu He, Yunhao Xie, Shiwei Zhang, Feng Xu, Jian Long*,Knowledge Assisted Hybrid Optimization Strategy of Large-Scale Crude Oil Scheduling Integrated Production Planning[J]. Computers and Chemical Engineering, 2025, 192: 108904.
11. Jian Long, Ning wang, Jiazi Zhai, Chen Liang, Siyi Jiang, Liang Zhao*. Data driven multi-objective economic-environmental robust optimization for refinery planning with multiple modes under uncertainty[J]. Computers & Industrial Engineering, 2024, 198: 110697.
12. Lei Wan, Yuhui Ruan, Jian Long*, Liang zhao, Tiantian Xu, Wang Ning. A Stackelberg Game-based Programming approach for Industrial Steam Systems Incorporating Renewable Energy Considering Demand Response[J]. Energy, 2024, 312: 133446.
13. Jian Long, Mengru Zhang, Anlan Li, Cheng Huang, Dong Xue*. Hybrid model of multimodal based on data enhancement and lumped reaction kinetics: Applying to industrial ebullated-bed residue hydrogenation unit[J]. Chin. J. Chem. Eng., 2025, 78: 284-302.
14. Jian Long, Long Ye, Haifei Peng, Zhou Tian*. Efficient prediction framework for large-scale nonlinear petrochemical process based on feature selection and temporal-attention LSTM: applied to fluid catalytic cracking[J]. Chemical Engineering Science, 2025, 301: 120733.
15. Guihua Hu, Qingfeng Tao, Rui Ying, Jian Long*. Multi-objective robust optimization design framework for low-pollution emission burners[J]. Chem. Eng. Res. and Des., 2024, 210: 180–189.
16. Jian Long, Yifan Chen, Liang Zhao*. Just-in-time learning method based on two kinds of local samples combined with two-stage training parallel learner for nonlinear chemical process soft sensing[J]. Measurement, 2024, 238: 115371.
17. Jian Long, Cheng Huang, Kai Deng, Lei Wan, Guihua Hu*, Feng Zhang. Novel hybrid data-driven modeling integrating variational modal decomposition and dual-stage self-attention model: applied to industrial petrochemical process[J]. Energy, 2024, 304: 131895.
18. Tiantian Xu, Jian Long*, Liang Zhao, and Wenli Du. Material and energy coupling systems optimization for large-scale industrial refinery with sustainable energy penetration under multiple uncertainties using two-stage stochastic programming[J]. Applied Energy, 2024, 371: 123525.
19. Haifei Peng, Jian Long*, Cheng Huang, Shibo Wei, Zhencheng Ye*. Multi modal hybrid modeling strategy based on Gaussian mixture variational autoencoder and spatial–temporal attention: Application to industrial process prediction[J]. Chemometr. Intell. Lab. Syst., 2024, 244: 105029.
20. Lei Wan, Kai Deng, Liang Zhao, Jian Long*. Multi-objective Optimization Strategy for Industrial Catalytic Cracking Units: Kinetic Model and Enhanced SPEA-2 Algorithm with Economic, CO2, and SO2 Emission Considerations[J]. Chemical Engineering Science, 2023, 282: 119331.
21. Tiantian Xu, Tianyue Li, Jian Long*, Liang Zhao, Wenli Du. Data-driven multi-period modeling and optimization for the industrial steam system of large-scale refineries [J]. Chemical Engineering Science, 2023, 282: 119112.
22. Yifan Chen, Anlan Li, Xiangyang Li, Dong Xue*, Jian Long*. Efficient JITL framework for nonlinear industrial chemical engineering soft sensing based on adaptive multi-branch variable scale integrated convolutional neural networks[J]. Advanced Engineering Informatics, 2023, 58: 102199.
23. LuYao Wang, Jian Long*, XiangYang Li, Haifei Peng, Zhencheng Ye*. Industrial units modeling using self-attention network based on feature selection and pattern classification[J]. Chem. Eng. Res. and Des., 2023, 200: 176-185.
24. Jian Long, Kai Deng, Renchu He*. Closed-loop scheduling optimization strategy based on particle swarm optimization with niche technology and soft sensor method of attributes-applied to gasoline blending process[J]. Chin. J. Chem. Eng., 2023, 61: 43–57.
25. Renchu He, Keshuai, Liang Zhao, Jian Long*. Minglei Yang*. Data-driven worst case model predictive control algorithm for propylene distillation column under uncertainty of top composition [J]. Journal of Process Control, 2023, 124: 199-213.