1.rsonal Information
Qiu Chaochao, PhD, lecturer, graduated from Huazhong University of Science and Technology with a major in Mechanical Engineering. He currently serves as the Deputy Department Head of the Mechanical Engineering Department at the DGUT-CNAM, a member of the Party Branch Committee of the faculty, and a core member of the National Intelligent Design and Numerical Control Technology Innovation Center-Dongguan University of Technology Joint Laboratory, Guangdong Provincial 3C Intelligent Equipment Innovation Team, and the Robot and Intelligent Equipment Innovation Center. He is also recognized as a "Third-Category Special Talent" in Dongguan. He has long been engaged in research on machine tool dynamics, vibration suppression, machining parameter optimization, thermal error prediction of machine tools, and industrial AI. He has presided over one youth project of the National Natural Science Foundation of China and has been invited to serve as a reviewer for several top journals such as Knowledge-Based Systems, IEEE/ASME Transactions on Mechatronics, and Journal of Industrial Information Integration. To date, he has published a total of 18 SCI/EI papers, including 5 first-tier Top papers as the first/corresponding author in prestigious international journals such as Mechanical Systems and Signal Processing, Engineering Applications of Artificial Intelligence, and Advanced Engineering Informatics. He has applied for/been granted 5 invention patents, won the first prize of the 2023 Innovation Dongguan Science and Technology Progress Award, the silver medal at the 49th International Exhibition of Inventions of Geneva, the gold medal at the 11th International Invention Exhibition "The Belt and Road" and BRICS Skills Development and Technological Innovation Competition, and the first prize of the Invention and Entrepreneurship Award of the China Invention Association in 2025.
2.Education
2018-09 - 2023.09 Huazhong University of Science and Technology PhD
2017-09 - 2018.07 Huazhong University of Science and Technology Master
3. Work Experience
Since September 2023, DGUT-CNAM, lecturer
4.Research Interests
1. Analysis of Machine Tool Dynamics Characteristics and Vibration Suppression
2. Prediction of Machine Tool Thermal Error Based on Data-driven Methods
3. Prediction of Machine Tool Tool Life Based on Deep Learning
5.Research Projects
[1]. National Natural Science Foundation of China for Young Scholars, Characterization and Vibration Suppression of Multi-Dimensional Coupled Dynamics of Group Machine Tools Based on Knowledge Graph and Meta-Learning, 2026.01 - 2028.12, Principal Investigator.
[2]. Project funded by the National Intelligent Design and Numerical Control Technology Innovation Center - Dongguan University of Technology Joint Laboratory, 2025.05 - 2028.05, Core Member.
[3]. Enterprise Contract, Thermal Error Compensation Technology Service for New 3C Drilling and Tapping Machine Spindle, 2024.01 - 2024.04, Participant.
6.Research Achievements
Papers：
[1]. Qiu, C., Liang, Q., Yin, L., Li, W., He, S., & Mao, X. (2025). Graph-based meta learning to predict tool tip dynamics of multiple machine tools with few labeled data. Mechanical Systems and Signal Processing, 237, 112991. (SCI，Top，IF= 8.9).
[2]. Qiu, C., Liang, Q., Yin, L., Bassir, D., Zhang, L., & Lin, W. (2025). A novel meta-learning-based spatio-temporal modeling approach for thermal error prediction of multiple machine tools with few labeled data. Engineering Applications of Artificial Intelligence, 162, 112706. (SCI，Top，IF= 8.0).
[3]. Liang, Q., Yin, L., Qiu, C., Zhang, L., Lin, W., Mao, X., & Mao, X. (2025). Thermal error prediction of different machine tools based on sequence-to-sequence hybrid domain alignment. Case Studies in Thermal Engineering, 106745. (SCI，Q1，IF= 6.4).
[4]. Yin, L., Hu, H., Zhang, L., Qiu, C., Lin, W., & Mao, X. (2025). Thermal error prediction of multiple machine tools using temperature sensor network and spatio-temporal graph transfer learning. IEEE Sensors Journal. (SCI，Q2，IF= 4.5).
[5]. Qiu, C., Yin, L., Mao, X., Zhang, L., & Zhang, F. (2025). A novel method based on knowledge graph to characterize cutting vibration under the coupling effect of varied cutting excitation and position-dependent dynamics. International Journal of Computer Integrated Manufacturing, 38(8), 1098-1125. (SCI，Q2，IF=4.0).
[6]. Zhou, M., Zhang, L., Qiu, C., & Yin, L. (2025). Research on the Z-direction thermal error modelling method based on an optimized CNN-BiLSTM-Attention. International Journal of Computer Integrated Manufacturing, 1-18. (SCI，Q2，IF=4.0).
[7]. Qiu C, Li K, Li B, et al. Semi-supervised graph convolutional network to predict position-and speed-dependent tool tip dynamics with limited labeled data[J]. Mechanical Systems and Signal Processing, 2022, 164: 108225. (SCI，Top，IF= 8.934).
[8]. Qiu C, Li K, Zhou X, et al. A novel method for signal labeling and precise location in a variable parameter milling process based on the stacked-BiLSTM-CRF and FLOSS[J]. Advanced Engineering Informatics, 2023, 55: 101850. (SCI，Top，IF= 7.862).
[9]. Li, W. , Hao, C. , He, S.* , Qiu, C.* , Liu, H. , & Xu, Y. , et al. Multi-agent reinforcement learning method for cutting parameters optimization based on simulation and experiment dual drive environment[J]. Mechanical Systems and Signal Processing, 2024, 216. (SCI，T类，IF= 8.4).
[10]. Qiu C, Li B, Liu H, et al. A novel method for machine tool structure condition monitoring based on knowledge graph[J]. The International Journal of Advanced Manufacturing Technology, 2022, 120(1-2): 563-582. (SCI，Q2，IF= 3.563).
[11]. Li K, Qiu C, Li C, et al. Vibration-based health monitoring of ball screw in changing operational conditions[J]. Journal of Manufacturing Processes, 2020, 53: 55-68. (SCI，Q2，IF= 5.684).
[12]. Li K, Qiu C, Zhou X, et al. Modeling and tagging of time sequence signals in the milling process based on an improved hidden semi-Markov model[J]. Expert Systems with Applications, 2022, 205: 117758. (SCI，T类，IF= 8.665).
[13]. Li K, Qiu C, Lin Y, et al. A weighted adaptive transfer learning for tool tip dynamics prediction of different machine tools[J]. Computers & Industrial Engineering, 2022, 169: 108273. (SCI，Q1，IF= 7.18).
[14]. Li, W., He, S., Mao, X., Li, B., Qiu, C., Yu, J., ... & Tan, X. Multi-agent evolution reinforcement learning method for machining parameters optimization based on bootstrap aggregating graph attention network simulated environment[J]. Journal of Manufacturing Systems, 2023, 67: 424-438. (SCI，Top，IF= 12.1).
[15]. Li, W., Li, B., He, S., Mao, X., Qiu, C., Qiu, Y., & Tan, X. A novel milling parameter optimization method based on improved deep reinforcement learning considering machining cost[J]. Journal of Manufacturing Processes, 2022, 84: 1362-1375. (SCI，Q1，IF= 6.2).
[16]. Li, W., Li, B., Wang, Z., Qiu, C., Niu, S., Tan, X., & Niu, T.. A drift detection method for industrial images based on a defect segmentation model[J]. Knowledge-Based Systems, 2024, 301: 112320. (SCI，Top，IF=7.2).
[17]. Zhang, F., Gu, Y., Yin, L., Song, J., Qiu, C., Ye, Z, et al. Research on the generation and evaluation of bridge defect datasets for underwater environments utilizing CycleGAN networks[J]. Expert Systems with Applications, 2025, 262: 125576. (SCI，Top，IF=7.5).
[18]. Qiu C, Mao X, Li W. A Novel Approach Based on Knowledge Graph and XGBoost to Characterize and Predict Position-and Speed-Dependent Dynamics of Machine Tool Structure[C]. Proceedings of the 3rd International Conference on Information Technologies and Electrical Engineering. 2020: 60-66. (EI).
Patents:
[1]. Qiu Chaochao; Su Hao; Yin Ling; Lin Weicheng; Zhang Lijuan. A Modeling Method for Machine Tool Thermal Error Based on Time Convolutional Network and Transfer Learning. (Accepted, Application No.: 202411843383.9)
[2]. Qiu Chaochao; Su Hao; Liang Qiongke; Yin Ling; Lin Weicheng; Zhang Lijuan; Hu Huaxin; Li Jiajun. A Spatio-Temporal Graph Modeling Method for Multi-Machine Tool Thermal Error Prediction Based on Meta-Learning. (Accepted, Application No.: 202511118853.X)
[3]. Qiu Chaochao; Li Weiye; Zhou Xinzao; Li Bin; Mao Xinyong; He Songping; Liu Hongqi; Peng Fangyu; Yu Fan. A Prediction Method for the Dynamic Characteristics of Machine Tool Tool Tip Based on Improved Graph Convolutional Network. (Patent No.: ZL 202110285492.3)
[4]. Zhou Xinzao; Li Kai; Shi Chengming; He Songping; Qiu Chaochao; Li Bin. An Online Identification Method for Chatter of CNC Machining Centers Based on Vibration Signals. (Patent No.: ZL 201911327809.4)
[5]. Qiu Chaochao; Li Bin; Yan Yifei; Gu Qiao; Cheng Shaojie. Training of Process Recommendation Model, Process Recommendation Method and Electronic Device. (Application No.: CN202210501295.5)
Competition Guidance：
[1]. In the 18th National 3D Digital Innovation Design Competition "Huazhong CNC Cup" for Industrial Collaborative Robots and Digital Twin Innovation Application Special Contest in 2025, the students were guided to win 1 third-place award at the national competition, 1 first-place award at the provincial competition, and 3 second-place awards at the provincial competition.
[2]. In the 17th National 3D Digital Innovation Design Competition "Huazhong CNC Cup" for Industrial Collaborative Robots and Digital Twin Innovation Application Special Contest in 2024, the students were guided to win the second-place award at the national competition.
7.Contact Information
Email:qiuchaochao@dgut.edu.cn
