We focus on Quality Control and Reliability Engineering of intelligent manufacturing and complex systems through engineering-informed machine learning and data analytics.
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Design of computer experiment, modeling and optimization: surrogate modeling, Bayesian optimization, uncertainty quantification.
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Data analytics for manufacturing system quality improvement: metal matrix nanocomposites fabrication; 3D printing, steel manufacturing; quality characterization and quantification; nondestructive inspection; modeling, monitoring and analysis for quality control and process improvement.
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Data-driven fault detection, diagnostics and prognostics of complex systems: integration of machine learning, statistical modeling and reliability theory for anomaly detection, diagnostics and prognostics of smart and connected systems, e.g., aero-engines.
数据驱动的复杂工业与服务系统质量与可靠性管理—以数据智能为核心，围绕产品设计、生产、运维等全生命周期管理，聚焦于仿真建模优化、质量管控、可靠性预测与维护。
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复杂仿真试验设计、建模与优化：代理模型构建、多精度与异构系统迁移学习、贝叶斯优化、不确定性量化、数字孪生
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先进制造系统质量管控：超强纳米复合材料制备、增材制造、特钢制造等过程建模与分析、在线异常检测与诊断、过程优化与控制
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高端装备与系统可靠性管理：面向航空发动机、电池、智能网联系统的建模、监测、诊断、健康评估预测、维护优化
We are looking for excellent and self-motivated MS and PhD students every year. 欢迎成绩优异（特别是数学成绩）的本科、硕士生加入我们实验室攻读硕士或博士学位！
Lab Director: Prof. Jianguo Wu （吴建国博士）
Contact（联系方式）:
Prof. Jianguo Wu
Department of Industrial Engineering and Management
College of Engineering, Peking University
Room 2040, Xinao Engineering Building (新奥工学大楼2040)
5 Yiheyuan Road, Haidian, Beijing, China 100871
Phone: 010-82529021
Email: j.wu[AT]pku.edu.cn
