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About Me (You Ling 凌游）

I am currently working as an Applied Scientist at Amazon, and my projects involve personalized search advertising and multilingual advertising technology. Prior to joining Amazon, I worked as a lead research engineer in the Probabilistics & Optimization Group at GE Global Research Center, Niskayuna, NY. My experience includes the development of advanced probabilistic modeling and machine learning tools to support multiple industries' (Aviation, Power, Renewable, Oil & Gas) asset performance management and service engineering. In addition, I have been the lead technical contributor to several research projects sponsored by AFRL/NASA Ames/NNSA/FAA, with focus on developing uncertainty quantification methods/codes for complex engineering systems.

Outside work, I enjoy reading, playing soccer and tennis, hiking, watching sports, skiing & snowboard.

Contact me: youlingvu (at) gmail.com

Find me on: Linkedin, Google Scholar, Github

Education

Vanderbilt University, PhD (2013) and MS (2011) in Civil Engineering (Reliability and Risk Engineering Program)

Shanghai Jiao Tong University, BS in Engineering Mechanics (2008)

Publication

PhD Dissertation

Uncertainty quantification in time-dependent reliability analysis [PDF]

Peer-reviewed Journal Papers

C. Li, S. Mahadevan, Y. Ling, S. Choze, and L. Wang. “Dynamic Bayesian Network for Aircraft Wing Health Monitoring Digital Twin”, AIAA Journal, 2017. [PDF]
J. G. Mullins, Y. Ling, S. Mahadevan, L. Sun, and A. H. Strachan, “Separation of aleatory and epistemic uncertainty in probabilistic model validation”, Reliability Engineering & System Safety, 2016. [PDF]
Y. Ling, J. G. Mullins, and S. Mahadevan, “Selection of model discrepancy priors in Bayesian calibration”, Journal of Computational Physics, 2014. [PDF]
Y. Ling, and S. Mahadevan, “Quantitative model validation techniques: new insights”, Reliability Engineering & System Safety, 2013. [PDF]
V. Hombal, Y. Ling, K. A. Wolfe, and S. Mahadevan, “Two-stage planar approximation to non-planar crack growth”, Engineering Fracture Mechanics, 2012. [PDF]
Y. Ling, and S. Mahadevan, “Integration of structural health monitoring and fatigue damage prognosis”, Mechanical Systems & Signal Processing, 2012. [PDF]
S. Sankararaman, Y. Ling, and S. Mahadevan, “Uncertainty quantification and model validation of fatigue crack growth prediction”, Engineering Fracture Mechanics, 2011. [PDF]
Y. Ling, C. Shantz, S. Mahadevan, and S. Sankararaman, “Stochastic prediction of fatigue loading using real-time monitoring data”, International Journal of Fatigue, 2011. [PDF]
S. Sankararaman, Y. Ling, C. Shantz, and S. Mahadevan, “Uncertainty quantification in fatigue crack growth prognosis”, International Journal of Prognostics and Health Management, 2011. [PDF]
S . Sankararaman, Y. Ling, C. Shantz, and S. Mahadevan, “Inference of equivalent initial flaw size under multiple sources of uncertainty”, International Journal of Fatigue, 2011. [PDF]
S. Sankararaman, Y. Ling, and S. Mahadevan, “Statistical inference of equivalent initial flaw size with complicated structural geometry and multi-axial variable amplitude loading”, International Journal of Fatigue, 2011. [PDF]

Conference Proceedings

Y. Ling, S. Ghosh, I. Asher, J. Kristensen, K. Ryan, and L. Wang. "An intelligent sampling framework for multi-objective optimization in high dimensional design space." AIAA SciTech 2018. [PDF]
S. Ghosh, I. Asher, J. Kristensen, Y. Ling, K. Ryan, and L. Wang. "Bayesian Multi-Source Modeling with Legacy Data." AIAA SciTech 2018. [PDF]
I. Asher, Y. Ling, and L. Wang. "Improving SIR with Constrained Resampling for Dynamic Bayesian Network Applications." AIAA SciTech 2018 [PDF]
J. Kristensen, I. Asher, Y. Ling, K. Ryan, A. Subramaniyan, and L. Wang. "Predictive analytics with an advanced Bayesian modeling framework" MODSIM World 2017. [PDF]
C. Li, S. Mahadeven, Y. Ling, L. Wang, and S. Choze. ”A dynamic Bayesian network approach for digital twin.” AIAA SciTech 2017. [PDF]
Y. Ling, I. Asher, L. Wang, F. Viana, and G. Khan. ”Information gain-based inspection scheduling for fatigued aircraft components.” AIAA SciTech 2017. [PDF]
I. Asher, G. Khan, L. Wang, Y. Ling, and F. Viana. "Calibrating an equivalent initial flaw size distribution from da/dN and S-N data." AIAA SciTech 2017. [PDF]
I. Asher, L. Wang, G. Khan, Y. Ling, and F. Viana. "Developing a Probabilistic Load Spectrum for Fatigue Modeling." AIAA SciTech 2017. [PDF]
J. Kristensen, Y. Ling, I. Asher, and L. Wang. ”Expected-Improvement-Based Methods for Adaptive Sampling in Multi-Objective Optimization Problems.” ASME IDETC/CIE 2016 [PDF]
Y. Ling, J. G. Mullins, and S. Mahadevan, “Options for the inclusion of model discrepancy in Bayesian calibration.” AIAA SciTech 2014. [PDF]
Y. Ling, and S. Mahadevan, “Bayesian networks for comprehensive uncertainty quantification in multi-scale, multiphysics risk analysis.” ICOSSAR 2013. [PDF]
Y. Ling, and S. Mahadevan, “Challenging issues in Bayesian calibration of multi-physics models.” AIAA SDM 2013. [PDF]
Y. Ling, and S. Mahadevan, "Interpretations, relationships, and application issues in model validation." AIAA SDM 2012. [PDF]

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