BRI Lab
Resilient and Intelligent Built Environment Lab
Texas Tech University
Resilient and Intelligent Built Environment Lab
Texas Tech University
Our group aims to integrate cutting-edge AI techniques with computing, design, and decision-making processes for large-scale structural and infrastructural systems. Our research interests encompass machine learning-based metamodeling, large-scale multi-hazard risk and resilience assessment, and AI-powered automated design, maintenance, and decision-making.
May 2025 Manish Basnet joins the BRI Lab as a undergraduate researcher, welcome!
Check out our new paper: Neural Operators for Stochastic Modeling of Nonlinear Structural System Response to Natural Hazards submitted to Engineering Structures!
Feb 2025 Daniel Willoughby joins the BRI Lab as a undergraduate researcher, welcome!
Jan 2025 Manisha Sapkota joins the BRI Lab as a Ph.D. student, welcome!
Nov 2024 Dr. Bowei Li is invited to give a guest lecture at the Michigan Technological University on "Performance-Based Wind Design for Engineered Buildings: Why and How".
Aug 2024 Dr. Bowei Li was invited to give a talk in the University of Miami CAE seminar series on "Efficient Performance Assessment for Large Scale Engineering Systems under Wind Hazards: Frameworks and Applications", check out the video record here!
Aug 2024 Check out our new paper: Deep learning enabled rapid nonlinear time history wind performance assessment published on Structures!
Aug 2024 Dr. Bowei Li joined Texas Tech University as an Assistant Professor at August 2024. Multiple Ph.D student opening will be available!
Jun 2024 Dr. Bowei Li attended the 7th AAWE workshop and presented "WiRA: A software for efficient reliability assessment and performance-based wind design."
May 2024 Dr. Bowei Li attended EMI/PMC 2024 and presented a colaborative work with JHU: "Neural Operators for Stochastic Modeling of System Response to Natural Hazards."
May 2024 Dr. Bowei Li attended EMI/PMC 2024 and presented: "Machine Learning with Knowledge Transfer for Rapid Estimation of Small Failure Probability of Large-scale Nonlinear Dynamic Systems."
Mar 2024 Our paper on Rapid Integration Schemes for Performance-Based Wind Engineering wins Best Paper Award for 2023 in Engineering Structures!
(Collaborative) Neural Operators for Stochastic Modeling of Nonlinear Structural System Response to Natural Hazards, arXiv
Deep learning enabled rapid nonlinear time history wind performance assessment, Structures
Reliability of inelastic wind excited structures by dynamic shakedown and adaptive fast nonlinear analysis (AFNA), Engineering Structures
Real-time forecast of hurricane-induced damage risk to envelope systems of engineered buildings through metamodeling, Journal of Wind Engineering and Industrial Aerodynamics
Metamodeling through Deep Learning of High-Dimensional Dynamic Nonlinear Systems Driven by General Stochastic Excitation, Journal of Structural Engineering