Dr Ji-Eun Byun
- Lecturer in Smart Sustainable and Resilient Infrastructure (Infrastructure & Environment)
telephone:
01413304109
email:
Ji-Eun.Byun@glasgow.ac.uk
Oakfield Avenue, Glasgow, Glasgow City, Scotland, United Kingdom, G12
Biography
Education
- 2020: MS/PhD in Civil and Environmental Engineering, Seoul National University, South Korea
Major in Structural and System Reliability Engineering
Dissertation Title: “Matrix-based Bayesian network for reliability assessment and decision making of complex large-scale systems”
Dissertation Advisor: Junho Song - 2015: BS in Civil and Environmental Engineering, Seoul National University, South Korea
Employment
- 2022 - present: Lecturer in Smart Infrastructure, James Watt School of Engineering, University of Glasgow
- 2021-2022: PDRA in Engineering Risk Analysis Group, Technical University of Munich, Germany
- Funded by Humboldt Research Fellowships for postdoctoral researchers
- Project title: Optimal predictive maintenance of large-scale civil systems (Advisor: Prof. Daniel Straub)
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- Research project: Tomorrow’s Cities funded by UKRI GCRF
- Research topic: Multi-hazard physical vulnerability of transport infrastructure (Advisor: Prof. Dina D’Ayala)2020-2021: PDRA in Civil, Environmental and Geomatic Engineering, University College London
Research interests
My expertise is probabilistic analysis and optimisation. Applications have dealt with civil engineering systems (e.g. structural systems and transportation networks), hazard risks (e.g. earthquakes), sensor data (e.g. weigh-in-motion data and structural health monitoring) and disaster inequality. By leveraging versatility of probability theory, I intend to expand applications to solve global challenges.
My research interests are two-fold: (1) discovering use of information/data and (2) facilitating interdisciplinary research/communication using probabilistic models. Examples of the first topic are (i) utilising sensor data for automatic decision systems of (infra)structures, (ii) performing reliability-based optimisation for expensive computational models (e.g. finite element analysis), (iii) formulating decision problems for engineering systems to cope with climate change and (iv) realising monetary gains from information. For the second topic, I envision to go beyond Engineering by integrating all disciplines including Social Sciences, Economics, Finance and Politics.
Supervision
If you are interested in the research topics above, please contact me via email.
Teaching
My teaching interests are
- probabilistic analysis and optimisation for engineering systems and
- machine learning and artificial intelligence.