MDASI Lab focuses modeling, monitoring and analysis of intelligent manufacturing processes and complex engineering systems for quality control, fault diagnosis and prognosis through integrated applications of sensing technology, engineering domain knowledge and machine learning/data analytics.

• Data analytics for manufacturing system 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.
• 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.
• Data analytics methodology development
  • deep learning;Bayesian inference; state-space models;particle filters; Gaussian process
  • online change-point detection; steady-state detection;
  • high-dimensional data fusion and monitoring;

• "Towards High-quality Intelligent Manufacturing—Quality Science Research under Industrial Big Data Environment", National Natural Science Foundation of China (Key Program of NSFC),PI: Dr. Kaibo Wang (Tsinghua University), PI: Dr. Jianguo Wu (Peking University) 01/2020-12/2024
• “End-Quench Hardenability Prediction and Control for 20CrMnTi Gear Steel Manufacturing”, HBIS Shijiazhuang Iron & Steel Co., Ltd, PI: Dr. Jianguo Wu,10/2018-05/2019
• “Online Process Monitoring and Quality Control of Additive Manufacturing based on Multiple Heterogeneous Sensors”, National Natural Science Foundation of China(regular NSFC grant), PI: Dr. Jianguo Wu, 01/2019-12/2022
• The Thousand Talents Plan for Distinguished Young Scholars, the Organization Department of China,2018-2021
• "Double-first class” grant for equipment acquisition, Peking University,2018
• "Double-first class” startup, Peking University,2018-2020
• "Advancement of Additive Manufacturing Process Monitoring and Metal Matrix Composite Fabrication”, Department of the Army MSDRC Program,PI: Dr. Jianguo Wu, PI: Dr. Ryan Wicker, 2017-2020
• "Ultrasonic Nondestructive Evaluation based Quality Inspection for Porosity Reduction in Metal-based Additive Manufacturing”, University Research Institute Grant, University of Texas Systems. 2016
• University of Texas Systems STARS Award, PI: Dr. Jianguo Wu, 2015-2017