PhD, Assistant Professor
Office: Room B210, College of Civil Engineering
Phone: +86-
Email: javayang@tongji.edu.cn
Department of Disaster Mitigation for Structures College of Civil Engineering
Tongji University Shanghai, China

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When I was young, I really wanted to change the system. You know, I was ready to fight. I was gonna be the best no matter what. You give an inch here, you give an inch there, you get caught up in the game. And then you realize that the system that you're trying to change - it changed you.
My Research Interests
My research interests generally include applied mathematics and computing science, where specifically I develop mathematical models of dynamic systems and efficient computational algorithms for identifying these models based on measured data. An important feature of my research is that I take a Bayesian approach for dynamic system identification so that both plausible models and the associated uncertainties can be identified given modeling assumptions and measured data. I have been developing advanced Markov chain Monte Carlo (MCMC) algorithms that find applications in dynamic system identification, or in general, optimization. Because no mathematical model can exactly represent a dynamic system in the real world, a true mathematical model does not exist and there will always be an uncertain prediction error. Moreover, non-unique models usually exist for a real-world dynamic system. A Bayesian framework is taken to address these problems. Instead of pinpointing a true model, multiple models in a parameter space are considered, with the posterior probability density function (PDF) of uncertain model parameters used as the measure of the relative plausibility of these models. The proposed MCMC algorithms are used to efficiently explore an extremely complex high-dimensional parameter space, and thus identify the posterior PDF. My research finds applications in model updating and operational modal analysis of full-scale civil engineering structures, robust response prediction, earthquake and wind engineering.
University Education
2006 - 2010 Bachelor of Engineering, Thermal Energy and Dynamics Engineering, School of Energy Science and Engineering, Central South University （中南大学）, China
2010 - 2015 Ph.D., Structural Engineering, Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong, China
Research Grants
National Natural Science Fund (国家自然科学基金), Principal Investigator, 2019-2021, National Natural Science Foundation of China (NSFC)
Project: Development of A New Fast Bayesian Method for Dynamic System Identification and Reliability Analysis
Shanghai Sailing Program （上海市科技人才项目“上海市青年科技英才扬帆计划”）, Principal Investigator, 2018-2021, Shanghai Science and Technology Committee (STCSM) (上海市科学技术委员会)
Project:A New Bayesian Method for Identification of Complex Structural Dynamic Models and Extreme Loads and Its Application for Structural Damage Detection
Fundamental Research Funds for the Central Universities (同济大学青年优秀人才培养行动计划), Principal Investigator, 2018-2019, Tongji University
Project:Development of A New Structural Damage Detection Method Based on Artificial Intelligence
Publications
1. Lam HF, Yang JH,Au SK. Bayesian model updating of a coupled-slab system using field test data utilizing an enhanced Markov chain Monte Carlo simulation algorithm. Engineering Structures 2015; 102: 144-155. (SCI, IF: 2.755. One of the most cited articles in Engineering Structures published since 2015)
2. Yang JH, Lam HF, Hu J. Ambient vibration test, modal identification and structural model updating following Bayesian framework. International Journal of Structural Stability and Dynamics 2015; 15(7): **. (SCI, IF: 2.082. One of the most cited articles in IJSSD published since 2015)
3. Lam HF, Yang JH,Au SK. Markov chain Monte Carlo‐based Bayesian method for structural model updating and damage detection. Structural Control and Health Monitoring 2018; 25(4):e2140. (SCI, IF: 3.622)
4. Yang JH, Lam HF. An efficient adaptive sequential Monte Carlo method for Bayesian model updating and damage detection. Structural Control and Health Monitoring 2018: e2260. (SCI, IF: 3.622)
5. Hu J, Yang JH. Operational modal analysis and Bayesian model updating of a coupled building. International Journal of Structural Stability and Dynamics 2018; DOI: 10.1142/S02**121. (SCI, IF: 2.082)
6. Lam HF, Yang JH,Hu Q, Ng CT. Railway ballast damage detection by Markov chain Monte Carlo-based Bayesian method. Structural Health Monitoring 2018; 17(3):706-724. (SCI, IF: 3.798)
7. Lam HF, Yang JH. Bayesian structural damage detection of steel towers using measured modal parameters. Earthquakes and Structures 2015; 8(4): 935-956. (SCI, IF: 1.309)
8. Lam HF, Hu J, Yang JH. Bayesian operational modal analysis and Markov chain Monte Carlo-based model updating of a factory building. Engineering Structures 2017; 132: 314-336. (SCI, IF: 2.755)
9. Lam HF, Alabi SA, Yang JH. Identification of rail-sleeper-ballast system through time-domain Markov chain Monte Carlo-based Bayesian approach. Engineering Structures 2017; 140: 421–436. (SCI, IF: 2.755)
10. Hu J, Lam HF, Yang JH. Operational modal identification and finite element model updating of a coupled building following Bayesian approach. Structural Control and Health Monitoring 2018; 25(2): e2089. (SCI, IF: 3.622)
11. Lam HF, Yang JH, Hu Q. How to install sensors for structural model updating? Procedia Engineering 2011; 14: 450–459. (EI)
12. Yang JH, Lam HF. Model updating based structural damage detection of transmission tower: Experimental verification by a scaled-model. Australian Journal of Multi-disciplinary Engineering 2013; 10(2): 129-144.
Services
Reviewer of the journals: Engineering Structures, Structural Control and Health Monitoring, Mechanical Systems and Signal Processing, Structural Health Monitoring, International Journal of Structural Stability and Dynamics
Chair and organizer of the mini-symposium Vibration Measurement, Modal Analysis and Model Updating of Structures in the Engineering Mechanics Institute Conference 2017 (EMI 2017), held at the Omni San Diego Hotel, San Diego, California, USA on June 4-7, 2017
Chair and organizer of the mini-symposium Bayesian Inference in System Identification: Efficient Algorithms and Applications in the Engineering Mechanics Institute Conference 2019 (EMI 2019), to be held at California Institute of Technology, Pasadena, California, USA on June 19-21, 2019