Research

RESEARCH Goal

"Our research team endeavors to introduce innovative methodologies, utilizing advanced AI techniques such as deep learning and sophisticated soft computing, to assess and retrofit existing structures. We propose novel ideas aimed at enhancing the resilience of structures, with a particular focus on next-generation performance-based design approaches."

Current RESEARCH areas

1. AI-Powered Sustainable Design: I lead research on integrating AI (Large Language Models, Quantum Machine Learning, Reinforcement Learning, Causal AI, and Explainable AI) into structural design workflows.  This focuses on optimizing building sustainability through Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) methodologies.

2. Smart Retrofitting of existing structures: Within this domain, my research explores the application of Machine Learning (ML) and Deep Learning (DL) techniques for Data-Driven Retrofitting Strategies and Cost-Effective Retrofitting Optimization of structures.

3. Predictive Maintenance of Structures: My research delves into harnessing the power of AI (including Deep Learning), Structural Health Monitoring (SHM), Digital Twins (DT), and Augmented Reality (AR) to support predictive maintenance practices for structures and infrastructure.

4. Structural Material Innovation:  I explore the application of Deep Learning and Computer Vision for investigating novel and "smart" structural materials. This research stream aims to unlock the potential of these materials for creating a more robust and sustainable infrastructure.

5. Next-generation performance-based design of structures for Seismic and Wind design of strucures..

RESEARCH INTERESTS

AI Advanced Techniques for Structural Engineering

1. Large Language Models,

2. Quantum Machine Learning

3. Explainable Artificial intelligence (XAI)

4. Deep Reinforcement Learning

5. Digital Twin for Structural Health monitoring of structures

6. Augmented reality (AR) applications for recyclability of structures

7. Automated Expert System for Life Cycle Assessment (LCA) for buildings

8. Automated Expert System Life Cycle Costing (LCC) for buildings

Soft computing techniques for seismic design and assessment 

1.  Deep learning for structural and earthquake engineering.

2.   AI applications on structural and seismic retrofitting of structures.

3.   ANN applications in structural and seismic engineering

4.   Soft computing in structural engineering

5.  Fuzzy inference systems in earthquake engineering.

6.  Seismic retrofitting and rehabilitation of structures.

7.  Machine learning techniques for seismic design of structures.

   Performance-based design of structures

1.  Seismic performance-based design of structures.

2.  Soil-pile structure interaction.

3.  Seismic life cycle cost.

5.  Seismic sensitivity analysis.

6.  Pushover techniques.

7.  Progressive collapse analysis.

8.  Seismic performance evaluation of offshore platforms.

9.  Retrofitting of offshore platforms.

10.   Seismic risk assessment.

11.   Seismic fragility of structures

12.   Blast analysis of offshore structures.

13.   Energy-based approaches for seismic design of structures.

14.   Self-centering systems.

15.   Energy dissipating devices.

16. Buckling-restrained braces.

SELECTED RESEARCH GRANTS

1)  Principal investigator (PI) of a research grant administered by the Korean National Research Foundation (Grant number: 2017032809). Research Project Name: Optimum Seismic Retrofit of Buildings using Combined Retrofit Techniques. Project Period: June 2017- March 2020. Budget: 150,000USD

2)  Co-investigator of a research grant funded by Ministry of Land, Infrastructure and Transport of Korean government, Technology Advancement Research Program (TARP). Grant# 17CTAP-C132889-01 Research Sub-Project Name: Retrofit of Buildings using Precast  Recentring Frames. Project Period: June 2016- March 2019. Budget: 730,000USD

3)  Co-investigator of a research grant administered by the Architecture and Urban Development Research Program, funded by Ministry of Land, Infrastructure and Transport of Korean government and Samsung Engineering Co., Ltd. Head office in south Korea. Grant number (13AUDP-B066083-01). Research Sub-Project Name: Retrofitting of Offshore Facilities. Project Period: June 2012- March 2015. Budget: 500,000USD