李新宇（Li Xinyu，Professor），1985年1月生，博士，湖北仙桃人，华中科技大学机械学院教授、博士生导师，青年长江学者、湖北省杰青，获全国优秀博士学位论文提名奖。现从事智能制造系统、车间调度、制造大数据分析、智能优化与机器学习等方面的科研工作。主持国家自然科学基金联合基金重点项目1项、面上/青年项目3项，国家重点研发计划课题1项等科研项目10余项；参与973课题、国家科技支撑计划、国家自然科学基金重点项目及企业委托课题等。出版专著5部，发表SCI论文100余篇，Web of Science他引4700余次，授权发明专利24项。担任IET Collaborative Intelligent Manufacturing（EI收录）Associate Editor、Sensors（SCI收录） Editorial Board Member、《工业工程》编委。担任中国机械工程学会工业大数据与智能系统分会总干事、湖北省机械工程学会工业工程专业委员会副理事长、湖北省运筹学会理事/副秘书长、中国仿真学会智能仿真优化与调度专业委员会副秘书长/常务委员、航天智能制造技术创新联盟智能系统与工业互联专业委员会委员等。获教育部自然科学一等奖1项、海洋科学技术二等奖1项、中国运筹学会“青年科技奖”提名奖、中国仿真学会智能仿真优化与调度专委会“青年科学家奖”、IFAC会刊EAAI Paper Prize Award (Practice、通讯作者)。 承担多项国家级科研项目，经费充足。重点开展制造系统调度、大数据分析等相关研究工作，研发智能车间核心工业软件，注重理论研究、方法创新与系统开发。欢迎机械工程、工业工程、自动化、计算机、软件工程、运筹学等方向的同学报考博士和硕士研究生。团队长期招聘相关方向的博士后，提供优厚待遇并注重人才的长期成长。

智能制造系统 车间调度 智能优化与机器学习

担任中国机械工程学会工业大数据与智能系统分会总干事、湖北省机械工程学会工业工程专业委员会副理事长、湖北省运筹学会理事/副秘书长、中国仿真学会智能仿真优化与调度专业委员会副秘书长/常务委员、航天智能制造技术创新联盟智能系统与工业互联专业委员会委员等。

1. Li X Y, Gao L, Pan Q K, Wan L, Chao K M. An effective hybrid genetic algorithm and variable neighborhood search for integrated process planning and scheduling in a packaging machine workshop. IEEE Transactions on Systems, Man and Cybernetics: Systems, 2019, 49(10): 1933-1944. 2. Li X Y, Lu C, Gao L, Xiao S Q, Wen L. An Effective Multi-Objective Algorithm for Energy Efficient Scheduling in a Real-Life Welding Shop. IEEE Transactions on Industrial Informatics, 2018, 14(12): 5400-5409. 3. Li X Y, Gao L, Wang W W, Wang C Y, Wen L. Particle swarm optimization hybridized with genetic algorithm for uncertain integrated process planning and scheduling with interval processing time. Computers & Industrial Engineering, 2019, 135: 1036-1046. 4. Li X Y, Xiao S Q, Wang C Y, Yi J. Mathematical Modeling and a Discrete Artificial Bee Colony Algorithm for the Welding Shop Scheduling Problem. Memetic Computing, 2019, 11: 371-389. 5. Li X Y, Gao L. An Effective Hybrid Genetic Algorithm and Tabu Search for Flexible Job Shop Scheduling Problem. International Journal of Production Economics, 2016, 174: 93-110. 6. Liu Q H, Li X Y*, Gao L. A Novel MILP Model Based on the Topology of a Network Graph for Process Planning in an Intelligent Manufacturing System. Engineering, 2021. 7. Liu Q H, Li X Y*, Gao L, Li Y L. A Modified Genetic Algorithm with New Encoding and Decoding Method for Integrated Process Planning and Scheduling Problem. IEEE Transactions on Cybernetics, 2020. 8. Wang K P, Gao L, Li X Y*, Li P G. Energy-Efficient Robotic Parallel Disassembly Sequence Planning for End-of-Life Products. IEEE Transactions on Automation Science and Engineering, 2021. 9. Wang Y C, Gao L, Li X Y*, Gao Y P, Xie X T. A New Graph-based Method for Class Imbalance in Surface Defect Recognition. IEEE Transactions on Instrumental Measurement, 2021, 70: 5007816. 10. Wen L, Gao L, Li X Y*, Zeng B. Convolutional Neural Network with Automatic Learning Rate Scheduler for Fault Classification. IEEE Transactions on Instrumental Measurement, 2021, 70: 3509912. 11. Gao Y P, Gao L, Li X Y*. A Generative Adversarial Network-based Deep Learning Method for Low-quality Defect Image Reconstruction and Recognition. IEEE Transactions on Industrial Informatics, 2021, 17(5): 3231-3240. 12. Gao Y P, Gao L, Li X Y*, Wang X. A Multi-Level Information Fusion-based Deep Leaning Method for Vision-based Defect Recognition. IEEE Transactions on Instrumentation & Measurement, 2020, 69(7): 3980-3991. 13. Lu C, Gao L, Li X Y*, Xiao S Q. A hybrid multi-objective grey wolf optimizer for dynamic scheduling in a real-world welding industry. Engineering Applications of Artificial Intelligence, 2017, 57: 61-79. 14. Wen L, Bo N, Ye X C, Li X Y*. A Novel Auto-LSTM based State of Health Estimation Method for Lithium-ion Batteries. Journal of Electrochemical Energy Conversion and Storage, Transactions of the ASME, 2021, 18: 030902. 15. Zhou Y Z, Yi W C, Gao L, Li X Y*. Adaptive differential evolution with sorting crossover rate for continuous optimization problems. IEEE Transactions on Cybernetics, 2017, 47(9): 2742-2753.