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

Import to contacts

ORCID iDhttps://orcid.org/0000-0003-0437-5013

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)
    • 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.

Publications

List by: Type | Date

Jump to: 2023 | 2022 | 2021
Number of items: 12.

2023

Byun, J.-E. , de Oliveira, W. and Royset, J. O. (2023) S-BORM: reliability-based optimization of general systems using buffered optimization and reliability method. Reliability Engineering and System Safety, 236, 109314. (doi: 10.1016/j.ress.2023.109314)

2022

Byun, J.-E. and D’Ayala, D. (2022) ResMapper: Matlab tool for seismic resilience mapping of large-scale road networks. SoftwareX, 20, 101249. (doi: 10.1016/j.softx.2022.101249)

Byun, J.-E. and D'Ayala, D. (2022) Seismic Resilience Mapping of Large-Scale Transportation Networks: Applications to Network in Istanbul, Turkey. 13th International Conference on Structural Safety & Reliability (ICOSSAR 2021-2022), Shanghai, China, 13-17 Sep 2022.

Byun, J.-E. and Straub, D. (2022) Active Learning of Deep Neural Networks for Reliability Analysis of Network Systems. 32nd European Safety and Reliability Conference (ESREL 2022), Dublin, Ireland, 28 Aug - 01 Sep 2022.

Byun, J.-E. and Royset, J. O. (2022) Data-driven optimization of reliability using buffered failure probability. Structural Safety, 98, 102232. (doi: 10.1016/j.strusafe.2022.102232)

Byun, J.-E. and Straub, D. (2022) Reliability Analysis of Transportation Networks Using Artificial Neural Networks. Engineering Mechanics Institute Conference 2022 (EMI 2022), Baltimore, MD, USA, 31 May - 03 Jun 2022.

Byun, J.-E. and D’Ayala, D. (2022) Urban seismic resilience mapping: a transportation network in Istanbul, Turkey. Scientific Reports, 12, 8188. (doi: 10.1038/s41598-022-11991-2) (PMID:35581236) (PMCID:PMC9114029)

Byun, J.-E. (2022) Physics-Informed Neural Networks for Traffic Assignment Optimization. The Applied Machine Learning Days (AMLD) at EPFL, Lausanne, Switzerland, 26-30 Mar 2022.

2021

Byun, J.-E. and Song, J. (2021) A general framework of Bayesian network for system reliability analysis using junction tree. Reliability Engineering and System Safety, 216, 107952. (doi: 10.1016/j.ress.2021.107952)

Royset, J. O. and Byun, J.-E. (2021) Gradients and subgradients of buffered failure probability. Operations Research Letters, 49(6), pp. 868-873. (doi: 10.1016/j.orl.2021.10.004)

Byun, J.-E. and Song, J. (2021) Generalized matrix-based Bayesian network for multi-state systems. Reliability Engineering and System Safety, 211, 107468. (doi: 10.1016/j.ress.2021.107468)

Byun, J.-E. (2021) Seismic Resilience Analysis of Urban Transportation Networks using Bayesian Network. 8th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COMPDYN 2021), 28-30 Jun 2021.

This list was generated on Wed Apr 24 20:50:32 2024 BST.
Jump to: Articles | Conference or Workshop Item
Number of items: 12.

Articles

Byun, J.-E. , de Oliveira, W. and Royset, J. O. (2023) S-BORM: reliability-based optimization of general systems using buffered optimization and reliability method. Reliability Engineering and System Safety, 236, 109314. (doi: 10.1016/j.ress.2023.109314)

Byun, J.-E. and D’Ayala, D. (2022) ResMapper: Matlab tool for seismic resilience mapping of large-scale road networks. SoftwareX, 20, 101249. (doi: 10.1016/j.softx.2022.101249)

Byun, J.-E. and Royset, J. O. (2022) Data-driven optimization of reliability using buffered failure probability. Structural Safety, 98, 102232. (doi: 10.1016/j.strusafe.2022.102232)

Byun, J.-E. and D’Ayala, D. (2022) Urban seismic resilience mapping: a transportation network in Istanbul, Turkey. Scientific Reports, 12, 8188. (doi: 10.1038/s41598-022-11991-2) (PMID:35581236) (PMCID:PMC9114029)

Byun, J.-E. and Song, J. (2021) A general framework of Bayesian network for system reliability analysis using junction tree. Reliability Engineering and System Safety, 216, 107952. (doi: 10.1016/j.ress.2021.107952)

Royset, J. O. and Byun, J.-E. (2021) Gradients and subgradients of buffered failure probability. Operations Research Letters, 49(6), pp. 868-873. (doi: 10.1016/j.orl.2021.10.004)

Byun, J.-E. and Song, J. (2021) Generalized matrix-based Bayesian network for multi-state systems. Reliability Engineering and System Safety, 211, 107468. (doi: 10.1016/j.ress.2021.107468)

Conference or Workshop Item

Byun, J.-E. and D'Ayala, D. (2022) Seismic Resilience Mapping of Large-Scale Transportation Networks: Applications to Network in Istanbul, Turkey. 13th International Conference on Structural Safety & Reliability (ICOSSAR 2021-2022), Shanghai, China, 13-17 Sep 2022.

Byun, J.-E. and Straub, D. (2022) Active Learning of Deep Neural Networks for Reliability Analysis of Network Systems. 32nd European Safety and Reliability Conference (ESREL 2022), Dublin, Ireland, 28 Aug - 01 Sep 2022.

Byun, J.-E. and Straub, D. (2022) Reliability Analysis of Transportation Networks Using Artificial Neural Networks. Engineering Mechanics Institute Conference 2022 (EMI 2022), Baltimore, MD, USA, 31 May - 03 Jun 2022.

Byun, J.-E. (2022) Physics-Informed Neural Networks for Traffic Assignment Optimization. The Applied Machine Learning Days (AMLD) at EPFL, Lausanne, Switzerland, 26-30 Mar 2022.

Byun, J.-E. (2021) Seismic Resilience Analysis of Urban Transportation Networks using Bayesian Network. 8th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COMPDYN 2021), 28-30 Jun 2021.

This list was generated on Wed Apr 24 20:50:32 2024 BST.

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.