地址：华东理工大学实验19楼413室
电话：021-64253720
邮箱：longjian@ecust.edu.cn
招生专业：控制科学与工程、控制工程、化学工程与技术
【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. Energy Conversion and Management、Expert Syst. Appl.、IEEE TII、IEEE TNSE、Fuel、JPC、CES、IECR等信息、能源、化工、控制领域20余本国际顶级/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. 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；
3. 科技部重点研发课题子课题，石油基乙烯流程工艺仿真共性技术平台，在研，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. 2018.03-2020.12，中央高校基本科研业务费专项资金-青年教师探索研究基金，工业混杂多变原油性质的近红外快速评价方法研究，结题，主持；
9. 上海市科委博士后人才计划. 基于工艺反应机理和能量流优化的炼厂调度系统研究，结题，主持；
10. 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。
【科研成果】
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，如化工AIChE Journal、Chem. Eng. Sci.(8篇)、Ind.& Eng. Chem. Res.(6篇)、Appl. Energy、Energy(5篇)、Fuel(2篇)、Expert Syst. Appl.(4篇)、Adv. Eng. Inf. (2篇)、Comput. Chem. Eng.(4篇)、Chin. J. Chem. Eng.(5篇)、Comput. Ind. Eng.等化工、能源、信息、人工智能领域顶级/著名期刊，发表了学术论文近100篇，其中SCI论文70余篇。公开和申请国家发明专利60余项，已授权26项；申请国际PCT专利5项，登记计算机软著作权50余项。
【育人成果】
在本科教学方面，讲授《专业外语》、《油气工程软件应用》、《化工自动化及仪表》、《输油管道设计与管理》、《天然气加工与工程》、《过程自动化及仪表》、《化工过程基本原理》等课程；连续多次被学生评教分在98分左右。完成了我校本科教学教育改革项目1项，发表教学论文1篇，参与校本科重点课程项目1项。
在科研育人方面，指导本科毕设课题、大学生创新课题、研究生毕业论文课题、竞赛项目、纵向/横向科研课题等科研项目超90项，覆盖学生120余人。指导本科生以第一完成人获学科创新省部级奖项2项，以第一作者身份发表EI会议学术论文2篇，以第一发明人申请发明专利1项，申请软件著作权6项。所直接指导的研究生：获得学术成果150余项（SCI论文40余篇，发明专利60余项，登记计算机软件著作权50余项）。学业奖学金一等率从入学的0%提升至研三的84.6%；获奖励和荣誉次数多、比例高(远高于学校评选比例)，如：国家/省部级竞赛3项，国家奖学金率37.5%(校评选比例4%左右)，市优秀毕业生率32.3%(校评选比例不超过5%)，优秀毕业生总比率达58.1%(校评选比例不超过10%)，校优秀毕业论文率52.6%。同时，学生们就业去向好，如：顶级央企、军工企业、互联网大厂、985高校读博士研究生。因此，自首届研究生毕业起，本人连续三年(2023年-2025年)获校优秀研究生指导教师。
【近年来发表的代表性论文】
1. Jian Long, RuiqiSong, LeiWan, WenzeGuo*. Two-stage multi-objective stochastic optimization of a wind-solar powered steam and green methanol co-production system[J]. AIChE Journal, 2026, e70475.
2. Dong Xue, Jicheng Tu, Yuan Guo, Jian Long*, Liang Zhao*. Multi-agent reinforcement learning for multi-objective optimization of crude distillation units.Chemical Engineering Science, 2026, 336:124520.
3. Jian Long*, Hengling Huang, Yuandian Lin, Jiawei Zhu, Yuhui Ruan*. Three-stage prediction framework based on series decomposition and spatial–temporal gated recurrent unit: Applied to fluid catalytic cracking process. Chemical Engineering Science, 2026, 336: 124482.
4. Jian Long, Xu Li, Luyao Wang, Guihua Hu*.A gated multimode transformer with feature-adaptive partitioning and cross-mode fusion for industrial flue gas emission prediction[J]. Chemical Engineering Science, 2026, 332: 124106.
5. 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.
6. Jian Long, Siyu Jiang, Jiazi Zhai, Wei Ma, Zhi Li*. Independent Exponential Slow Feature Analysis for Fine-scale Monitoring Multimode Processes: Application to Nonstationary Crude Distillation Units. Chemical Engineering Science, 2025, 316: 121909.
7. 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.
8. 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.
9. 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.
10. Chen Fan, Haodong Xu, Xindong Wang, Jian Long*. VAE-driven feature learning with context-aware attention and ResNet gradient optimization: applied to industrial hydrocracking processes[J]. Industrial & Engineering Chemistry Research, 2026, 65(9): 5087–5110.
11. Kai Luo, Haifei Peng, Bing Wang, Wenze Guo, Renchu He*，Jian Long*. Gated Recurrent Knowledge-Guided Attention Network with Adaptive Graph Structure Learning in Industrial Process. Industrial & Engineering Chemistry Research, 2025, 64, 41, 19924-19936.
12. Jian Long, Jiawei Zhu, Ning Wang, Kai Luo, Yejie Zhao, Yunmeng Zhao*.Neural ordinary differential equation and supervised gated recurrent units embedded with historical variables for petrochemical process prediction. Industrial & Engineering Chemistry Research, 2025, 64, 41, 20070–20088.
13. 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.
14. 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.
15. Jian Long, Bin Wang, Haifei Peng, Hengmin Zhang. A Multi-Source Attention Graph Neural Network for modeling long and short-term dependencies in chemical process forecasting. Advanced Engineering Informatics, 2026, 71: 104395.
16. Kaipeng Zhang, Jian Long*, Yuhui Ruan*, Cheng Huang, Liang Zhao. MINLP-based optimization of multi–flow coupling system for FCC–steam system–renewable energy integration toward methanol synthesis from captured CO2. Energy, 2026, 351:140722.
17. 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.
18. 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.
19. 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.
20. 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.
21. 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.
22. Jian Long, Qiulei Xue, Long Ye, Yanxia Xu*. A condition-driven hybrid GRU-GMCVAE framework for dynamic anomaly detection: Application to industrial petrochemical processes. Expert systems with applications, 2026, 305, 130804.
23. Wenbin Du, Jian Long*, Zhu Cao*. Low-light Image Enhancement via Multi-scale Attention combined with Fourier Transform[J].Expert Systems With Applications, 2026, 321:132146.
24. 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.
25. Changcheng Zhao, Yuhui Ruan, Jiazi Zhai, Haifei Peng, Jian Long*, Guihua Hu*. Dual decomposition-enhanced integrated deep networks with bidirectional CNN and semi-supervised GRU for multivariate nonlinear time series forecasting, Information Sciences, 2026, 735:123020.
26. Chensheng Liu, Yongyu Li, Yang Yu, Xiaoming Wu, Ming Yang, Yang Tang, Jian Long*. Spatiotemporal Stealthy Attacks in Power Systems with High Penetrated Renewable Energy Sources. IEEE Internet of Things Journal, 2025，235(12): 1114-51124.
27. Hengling Huang, Kai Deng, Luyao Wang, Wenze Guo, Jian Long*. Reaction kinetics-guided multi-mode feature fusion Transformer for pollutant concentration prediction[J].Journal of Environmental Chemical Engineering, 2026, 14: 123378.
28. Bin Wang, Kai Luo, Xiangming Chen, Kai Deng, Wenze Guo*, Jian Long*. Multi-strategy modeling integrating kinetics mechanism of cracking and pyrolysis and unsupervised dual-stage attention long and short-term memory network. Fuel process technology, 2025, 279: 108349.
29. 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
30. Jian Long, Bishi Zhao, Kai Deng, Cheng Huang, Chen Fan*. MINLP-Based Integrated Modeling and Multi-Period Optimization of Mass-Energy Coupled FCC-Steam Systems with Carbon-Cost-Oriented Economic Objective, Computers and Chemical Engineering, 2026, 206: 109503.
