Xiaoping Du

Xiaoping Du

Professor of Mechanical Engineering

Location: Indianapolis

SL 260G
723 W Michigan St
Indianapolis, IN 46202
duxp@purdue.edu
Phone: 765-495-7787

Degrees

  • Ph.D. Mechanical Engineering, University of Illinois at Chicago, 04/2002

Research Interests

  • Design optimization
  • Probabilistic and statistical methods
  • Reliability-based and robust design
  • Uncertainty quantification for machine learning

Fundamental Research Area(s)

Awards and Recognitions

  • 2023, Trustees' Teaching Award, Indiana University–Purdue University Indianapolis
  • 2021, Associate Editor Award, Journal of Mechanical Design, ASME
  • 2017, Appointed as Curators' Distinguished Professor in University of Missouri System
  • 2017, Governor's Award for Excellence in Education (Missouri)
  • 2016, Elected as fellow of ASME
  • 2016, Outstanding Teaching Award, Missouri University of Science and Technology
  • 2015, Faculty Teaching Award, Missouri University of Science and Technology
  • 2014, Outstanding Teaching Award, Missouri University of Science and Technology
  • 2013, Teaching Excellence commendation, Missouri University of Science and Technology
  • 2013, Faculty Excellence Award, Missouri University of Science and Technology
  • 2012, Faculty Teaching Award, Missouri University of Science and Technology
  • 2012, Pi Tau Sigma Silver Slide Rule Award for Teaching
  • 2010, Outstanding Teaching Award, Missouri University of Science and Technology
  • 2006-2008, Dean's Teaching Scholar, University of Missouri - Rolla
  • 2006, Outstanding Teaching Award, University of Missouri - Rolla
  • 2006, Faculty Excellence Award, University of Missouri - Rolla
  • 2005, Outstanding Teaching Award, University of Missouri - Rolla
  • 2005, Excellence in Teaching Award, School of Engineering, University of Missouri - Rolla
  • 2005, Innovative Teaching Award, School of Engineering, University of Missouri - Rolla
  • 2005, AMAE (Academy of Mechanical and Aerospace Engineers) Faculty Excellence Award, University of Missouri – Rolla

Selected Publications

Jin, J, Hu, Z, Du, X, “Uncertainty Quantification with Mixed Data by Hybrid Convolutional Neural Network for Additive Manufacturing,” accepted by ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 2024

Du, X, “Accounting for Machine Learning Prediction Errors in Design." ASME Journal of Mechanical Design, 146(5): 051709, 2024, doi.org/10.1115/1.4064278

Wu, H, Du, X, “Time-and Space-Dependent Reliability-Based Design with Envelope Method,” ASME Journal of Mechanical Design, 145(3): 031708, 2023, doi: 10.1115/1.4056599

Li, H, Du, X, “Recovering Missing Component Dependence for System Reliability Prediction via Synergy Between Physics and Data,” ASME Journal of Mechanical Design, 44(1): 041701, 2022, doi: 10.1115/1.4052624

Wu, H, Du, X, “Envelope Method for Time-and Space-Dependent Reliability Prediction,” ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B, 8(4): 041201, 2022, doi: 10.1115/1.4054171

Meng, L., Du, X., McWilliams, B, Zhang, J, “Probabilistic Feasibility Design of a Laser Powder Bed Fusion Process Using Integrated First-Order Reliability and Monte Carlo Methods," ASME. Journal of Manufacturing Science and Engineering, 143(9): 091004, 2021, doi: 10.1115/1.4050544

Shen, D, Yin, J, Du, X., Li, L., “Distributed Stochastic Model Predictive Control with Taguchi's Robustness for Vehicle Platooning,” IEEE Transactions on Intelligent Transportation Systems, 23(9): 15967 – 15979, 2022, doi: 10.1109/TITS.2022.3146715

Yin, J, Du, X, “Active Learning with Generalized Sliced Inverse Regression for High-Dimensional Reliability Analysis,” Structural Safety, 94: 102151, 2022, doi: 10.1016/j.strusafe.2021.102151

Hu, Z, Hu Z, Du X, “One-class Support Vector Machines with a Bias Constraint and Its Application in System Reliability Prediction,” Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 33(3):346-358, 2019, doi:10.1017/S0890060419000155

Du, X, Chen, W, “Sequential Optimization and Reliability Assessment Method for Efficient Probabilistic Design,” ASME Journal of Mechanical Design, 2004; 126(2): 225–233, doi.org/10.1115/1.1649968