
研究方向:
智能设计、多学科优化设计、知识数据融合的智能优化等
教育背景:
2012.09-2016.06 北京理工大学 本科 工业工程
2016.09-2018.02 北京理工大学 硕博连读 机械工程
2018.02-2018.11 美国俄克拉荷马大学 访问学者 系统实现实验室
2018.11-2023.6 北京理工大学 硕博连读 机械工程
工作经历:
2023.9-至今 北京理工大学长三角研究院(嘉兴)
学术成果:
主持国家科技重大专项课题、参与重点研发计划青年科学家、国自然青年基金等国家级、省部级项目6项,中国机械工程学会—机械设计分会青年委员。在Journal of Intelligent Manufacturing, Advanced Engineering Informatics, Energy,《计算机集成制造系统》等领域顶级及重要期刊和会议上发表学术论文14篇,申请授权国家发明专利14项,授权软件著作权4项,参编专著2部。
[1] 贾良跃,郝佳,商曦文等, 基于长短期记忆网络的桁架车身结构轻量化设计优化. 计算机集成制造系统 ,2023, 29(10):3317-3330.
[2] 贾良跃,郝佳,孙治斌等, 一种白车身结构工艺参数优化模型训练、应用方法及装置[P]: 中国,CN202510096717.9.
[3] Liangyue Jia, Reza Alizadeh and Farrokh Mistree, A rule-based method for automated surrogate model selection. Advanced Engineering Informatics, 2020, 45: 101-123.
[4] Reza Alizadeh, Liangyue Jia and Farrokh Mistree, Ensemble of surrogates and cross-validation for rapid and accurate predictions using small data sets. AI EDAM, 2019, 33(4): 484-501.
[5] Hao Jia, Wenbin Ye, and Liangyue Jia. Building surrogate models for engineering problems by integrating limited simulation data and monotonic engineering knowledge. Advanced Engineering Informatics 2021,(49): 101342.
[6] Hao Jia, Liangyue Jia, and Yan Yan. Design optimization by integrating limited simulation data and shape engineering knowledge with Bayesian optimization (BO-DK4DO). Journal of Intelligent Manufacturing, 2020,31(8), 2049-2067.
[7] 李作轩,贾良跃,郝佳等, 基于多工况关联的无人车辆车身结构轻量化优化设计. 兵工学报, 44(11), 3529-3542.
[8] Liangyue Jia and Jia Hao, A reinforcement learning based blade twist angle distribution searching method for optimizing wind turbine energy power. Energy, 2021, 215: 119148.
[9] Jia Hao, Ruofan Deng, Liangyue Jia*, Human-in-The-Loop Optimization for Vehicle Body Lightweight Design, Advanced Engineering Informatics, 2024, 62:102887
[10] Jie You, Yonghong Zhao and Liangyue Jia*, A fast crashworthiness assessment framework: Sectional force-based multi-stage physics informed surrogate model. Advances in Engineering Software, 2026, 213: 104090.
[11] Sun, Zhibin, Liangyue Jia*, Jia Hao, Zuoxuan Li, Ruofan Deng, and Nan Wang. KT-MDO: a knowledge-template-driven multidisciplinary design optimization framework. Advances in Engineering Software, 214 (2026): 104105.
教学工作:
负责或指导学生获得包括全国“互联网+”创新创业大赛银奖,“挑战杯”全国大学生创业大赛银奖等在内的国家级、省部级奖励11项。
社会兼职:
中国机械工程学会—机械设计分会青年委员,“工业知识与数据融合应用工业和信息化部重点实验室”核心成员,Journal of Intelligent Manufacturing,Advanced Engineering Informatics等期刊长期审稿。