轨道交通信号与控制

智能测控、故障预测与健康管理、机器学习、计算机视觉

1. 2004/09-2007/07，中国科学院研究生院/中科院自动化研究所，博士。
2. 1999/09-2002/07，华北工学院，自动控制系，硕士。
3. 1993/09-1997/07，华北工学院，自动控制系，学士。

1. 1997/06-至今，中北大学，电气与控制工程学院，教师.
2. 2014/01-2015/01，Industry Control Center，University of Strathclyde, UK，访问学者.

中国自动化学会会员
中国仿真学会会员

1. Xia G, Jia C, Shi Y, Jia J, Pang X, Wen J, Zeng J. Remaining useful life prediction of lithium-ion batteries by considering trend filtering segmentation under fuzzy information granulation[J]. Energy, 318(1):134810, 2025.
2. Ren X, Jia J, Pang X, Shi Y, Wen J, Zeng J. Traffic Flow Prediction through a Hybrid CLSTM Model with Multifeature Fusion[J]. Journal of Transportation Engineering, Part A: Systems, 150(12):04024084, 2024.
3. Cui S, Jia J, Pang X, Wen J, Shi Y, Zeng J. A data-driven method with sample entropy and CEEMDAN for short-term performance degradation prediction of dynamic hydrogen fuel cells[J]. International Journal of Hydrogen Energy, 83:916–32, 2024.
4. Zhang W, Jia J, Pang X, Wen J, Shi Y, Zeng J. An Improved Transformer Model for Remaining Useful Life Prediction of Lithium-Ion Batteries under Random Charging and Discharging[J]. Electronics, 13, 1423, 2024.
5. Zhang J, You J, Jia J, Zhang W, Ren X. Small Target Defects Detection of Aluminum Plates Surface Using an MSN-YOLOv5 Model[C]. Chinese Conference on Pattern Recognition and Computer Vision (PRCV 2024), Xinjiang, Wulumuqi, 2024.
6. Cheng G, Jia J, Pang X, Wen J, Shi Y, Zeng J. DFE-SLAM: Dynamic SLAM based on improved feature extraction[C]. 2024 China Automation Congress (CAC), Shandong, Qingdao, 2024.
7. J. Jia, Y. Wang, and H. Yue. Design of sliding mode controller based on radial basis function neural network for spacecraft autonomous proximity[C]. IFAC-PapersOnLine, 56(2): 2456–2461, 2023.
8. Jia J, Zhang H, Zhang W, et al. Interval Prediction of Lithium-Ion Battery Health State Based on Charging Feature Fusion and LSTMQR[C]. 2023 China Automation Congress (CAC), Chongqing, 2023.
9. You J, Jia J, Zhang W, et al. A Location Selection Method for Infected Areas Material Distribution Based on SIR Model and GA-K - means Algorithm[C]. 2023 China Automation Congress (CAC), Chongqing, 2023.
10. Jia C, Tian Y, Shi Y, Jia J, et al. State of health prediction of lithium-ion batteries based on bidirectional gated recurrent unit and transformer[J]. Energy, 285: 129401, 2023.
11. Pang X, Zhao Z, Wen J, Jia J, et al. Considering the self-adaptive segmentation of time series in interval prediction of remaining useful life for lithium-ion battery[J]. Journal of Energy Storage, 70: 107862, 2023.
12. A Novel Multi-Robot Task Assignment Scheme Based on a Multi-Angle K-Means Clustering Algorithm and a Two-Stage Load-Balancing Strategy[J]. Electronics, 12(18):3842, 2023.
13. Jia J, Yuan S, Shi Y, et al. Improved sparrow search algorithm optimization deep extreme learning machine for lithium-ion battery state-of-health prediction[J]. Iscience, 25(4): 103988, 2022.
14. Pang X, Zhao Z, Wen J, Jia J, et al. An interval prediction approach based on fuzzy information granulation and linguistic description for remaining useful life of lithium-ion batteries[J]. Journal of Power Sources, 542: 231750, 2022.
15. Jia J, Wang K, Shi Y, et al. A multi-scale state of health prediction framework of lithium-ion batteries considering the temperature variation during battery discharge[J]. Journal of Energy Storage, 42: 103076, 2021.
16. Jia J, Wang K, Pang X, et al. Multi‐Scale prediction of RUL and SOH for Lithium‐Ion batteries based on WNN‐UPF combined model[J]. Chinese Journal of Electronics, 30(1): 26-35, 2021.
17. Pang X, Liu X, Jia J, et al. A lithium-ion battery remaining useful life prediction method based on the incremental capacity analysis and Gaussian process regression[J]. Microelectronics Reliability, 127: 114405, 2021.
18. Jia J, Liang J, Pang X, et al. SOH and RUL prediction of lithium-ion batteries based on Gaussian process regression with indirect health indicators[J]. Energies, 13(2): 375, 2020.

1.国家自然科学基金面上项目,考虑预测可信度评估的多部件系统预测维修与备件库存联合决策研究,2021/01- 2024/12, 参与。
2.山西省科技重大专项子项目, 车系统试验研究, 2021/09- 2024/12，主持。
3.山西省重点研发计划项目,风力发电机组的大数据系统及应用服务平台研发,2018/01-2022/12,参与。
4.山西省留学回国人员资助项目，基于多尺度深度神经网络的锂电池健康状态预测研究，2021/01- 2023/12，主持。
5.山西省重点实验室基金，随机充放电状况下的锂电池健康状态预测，2022/08- 2024/08，主持。
6.山西省“1331工程”成果转化专项，可重构锂电池管理系统的设计，2021/01- 2021/12，主持。
7.国家自然科学基金，高超声速飞行器舵机负载模拟器的动态特性研究，2014/01-2017/12，参与。
8.山西省研究生教学改革项目，轨道交通运输专业研究生产教融合协同育人模式探索与实践，202408-202608，主持。

1. 一种基于ISSA耦合DELM的锂离子电池健康状态预测方法, ZL202111311076.2
2. 一种多尺度锂离子电池健康状态的预测方法, ZL202110851950.5
3. 多类型锂离子电池组管理系统的健康状态和剩余寿命预测方法, ZL202010800353.5
4. 同类型不同锂离子电池剩余使用寿命预测方法和系统，ZL201810989186.6
5. 一种双电机驱动的负载模拟器,ZL201410145238.3.

中国兵器工业总公司科学技术三等奖、山西省科技进步奖二等奖、中北大学师德先进个人。