贺松平（He Songping，Research Fellow），华中科技大学机械电子工程专业博士，密歇根大学迪尔本分校博士后，现为华中科技大学机械科学与工程学院研究员。兼任中国人工智能学会智能制造专业委员会副秘书长、湖北省机械工程学会机械工业自动化专业委员会理事。主要从事智能制造技术、高端电子制造装备、智能辅助诊疗方面的研究。先后主持及承担国家自然科学基金、国家重点研发计划子课题、湖北省重点研发计划、湖北省自然科学基金、武汉市科技晨光计划等项目。发表SCI收录论文二十余篇，申请发明专利三十余项。

智能制造技术 高端电子制造装备

主要从事高端电子制造装备、智能制造技术方面的研究

[1] Multi-agent evolution reinforcement learning method for machining parameters optimization based on bootstrap aggregating graph attention network simulated environment, Journal of Manufacturing Systems, 2023, 67: 424-438. [2] A novel method for signal labeling and precise location in a variable parameter milling process based on the stacked-BiLSTM-CRF and FLOSS, Advanced Engineering Informatics, 2023, 55: 101850. [3] A novel milling parameter optimization method based on improved deep reinforcement learning considering machining cost, Journal of Manufacturing Processes, 2022, 84: 1362-1375. [4] Research on the Modelling and Development of Flexibility in Production System Design Phase Driven by Digital Twins, Applied Sciences, 2022, 12(5): 2537. [5] A novel online chatter detection method in milling process based on multiscale entropy and gradient tree boosting, Mechanical Systems and Signal Processing, 2020, 135: 106385. [6] Bayesian uncertainty quantification and propagation for prediction of milling stability lobe, Mechanical Systems and Signal Processing, 2020, 138: 106532. [7] Tool Wear Prediction via Multidimensional Stacked Sparse Autoencoders With Feature Fusion, IEEE Transactions on Industrial Informatics, 2020, 16(8): 5150-5159. [8] Online chatter detection in milling process based on VMD and multiscale entropy, The International Journal of Advanced Manufacturing Technology, 2020, 105(12): 5009-5022.