Publications

Transformer-based automatic tracking of structural crack propagation

Zuo H, Wang T, Mei Q

Structural Control and Health Monitoring (Accepted), 2026

Seismic response prediction for timber braced frames using machine learning: performance, explainability, and integration into fragility analysis

Nguyen HD, Cheshmehkaboodi N, Mei Q, Daneshvar H, Chui YH

Journal of Structural Design and Construction Practice (Accepted), 2026

TrajGATFormer: a graph-based transformer approach for worker and obstacle trajectory prediction in off-site construction environments

Alduais M, Li X, Mei Q

Advanced Engineering Informatics, vol. 73, pp. 104583, 2026

A Fast and Accurate Phase-Based Displacement Measurement Method Based on Complex Laplacian Pyramid with Condensed Focus Frequency

Ai S, Dong CZ, Mei Q

Computer-Aided Civil and Infrastructure Engineering, pp. 100023, 2026

An integrated architecture for fixed truck assignment optimization in open-pit mines: synergistic optimization, hybrid modeling, and multi-objective optimization

Xu H, Zhao H, Lu J, Zuo H, Zheng W, Guo P, Yang D, Zhang B, Mei Q

Applied Energy, vol. 404, pp. 127170, 2026

Harnessing nearshoring for energy justice: a fuzzy TOPSIS-based framework for equitable energy transition in Mexico

Briceño CP, Ponce P, Martínez DLR, Mei Q, Castellanos S, Fayek AR

Environmental Research: Energy, vol. 3, no. 1, pp. 015005, 2026

Human-centered design and development framework for autonomous inspection robot systems in lean construction 4.0

Wang Z, Mei Q, Lee G, Bock T, Gonzalez VA

Engineering, Construction and Architectural Management, vol. 33, no. 2, pp. 937-962, 2026

Prediction of pipeline strain demand under ground movement using a neural network–enhanced finite difference method

Ji B, Mei Q, Yoosef-Ghodsi N, Adeeb S

Engineering Structures, 346, vol. 346, pp. 121623, 2026

A genetic algorithm-based calibration procedure for hysteresis loops in timber structures

Nguyen HD, Mei Q, Chui YH

Engineering Structures, vol. 346, pp. 121622, 2026

Table comprehension in building codes using vision language models and domain-specific fine-tuning

Aqib M, Hamza M, Mei Q

arXiv preprint arXiv:2511.18306, 2025

Monte Carlo tree search for mass timber building design optimization

Sarothi SZ, Nguyen HD, Mei Q, Chui YH

Computer-Aided Civil and Infrastructure Engineering, vol. 40, no. 31, pp. 6242-6260, 2025

Automating structural engineering workflows with large language model agents

Liang H, Zhou Y, Talebi-Kalaleh M, Mei Q

arXiv preprint arXiv:2510.11004, 2025

AI-assisted 3D model generation for discontinuum-based analysis of URM buildings

Griesbach P, Farcasiu A, Wilson R, Mei Q, Pulats B

Structures, vol. 81, pp. 110371, 2025

Multi-bridge inference structural health monitoring (MISHM): a drive-by crowdsensing approach at the network level

Zeng J, Mei Q, Gül M

Structural Control and Health Monitoring, vol. 2025, pp. 8624965, 2025

AI applications for structural design automation

Xie H, Mei

Automation in Construction, vol. 179, pp. 106496, 2025

Fine-tuning large language models and evaluating retrieval methods for improved question answering on building codes

Aqib M, Hamza M, Mei

Smart Construction, vol. 2, no. 3, pp. 0021, 2025

A Transformer-based approach for similar layout retrieval and difference detection in architectural drawings of wood frame buildings

Xie H, Mei

Journal of Building Engineering, vol. 111, pp. 113438, 2025

Crowdsensing-based bridge vibration monitoring using a sparse network of random mobile sensors: theory and numerical verifications

Talebi-Kalaleh M, Gül M, Mei

Journal of Sound and Vibration, vol. 618, pp. 119289, 2025

Transfer learning for lateral capacity prediction of monopile foundations with limited data

Alduais M, Mei Q, Taherkhani A

Computers and Geotechnics, vol. 185, pp. 107359, 2025

A type-2 fuzzy logic expert system for AI selection in solar photovoltaic applications based on data and literature-driven decision framework

Briceño CP, Ponce P, Fayek AR, Mei, Q

Processes, vol. 13, no. 5, pp. 1524, 2025

Integrating large language models for automated structural analysis

Liang H, Talebi-Kalaleh M, Mei Q

arXiv preprint arXiv:2504.09754, 2025

Using vision language models for safety hazard identification in construction

Adil M, Lee G, Gonzalez VA, Mei Q

arXiv preprint arXiv:2504.09083, 2025

Ensemble learning of deep CNN models and two stage level prediction of cobb angle on surface topography in adolescents with idiopathic scoliosis

Hassan M, Ruiz JMG, Mohamed N, Burke TN, Mei Q, Westover L

Medical Engineering & Physics, vol. 140, pp. 104332, 2025

Optimizing solar PV deployment in manufacturing: a morphological matrix and fuzzy TOPSIS approach

Briceño CP, Ponce P, Fayek AR, Anthony B, Bradley R, Peffer T, Meier A, Mei, Q

Processes, vol. 13, no. 4, pp. 1120, 2025

The optimal scale level of complex steerable pyramid for phase-based motion estimation under different motion ranges and target sizes

Ai S, Dong CZ, Mei Q

Measurement, vol. 253, pp. 117440, 2025

The framework and implementation of using large language models to answer questions about building codes and standards

Joffe Z, Felobes G, Elgouhari Y, Talebi-Kalaleh M, Mei Q, Chui YH

Journal of Computing in Civil Engineering, vol. 39, no. 4, pp. 05025004, 2025

Three-dimensional markerless surface topography approach with convolutional neural networks for adolescent idiopathic scoliosis screening

Mohamed N, Ruiz JMG, Hassan M, Costa OA, Burke TN, Mei Q, Westover L

Scientific Reports, vol. 15, no. 1, pp. 8728, 2025

Sensor adoption in the construction industry: barriers, opportunities, and strategies

Wang Z, González VA, Mei Q, Lee G

Automation in Construction, vol. 170, pp. 105937, 2025

A semi-supervised approach for building wall layout segmentation based on transformers and limited data

Xie H, Ma X, Mei Q, Chui YH

Computer-Aided Civil and Infrastructure Engineering, vol. 40, no. 10, pp. 1295-1313, 2025

ErgoChat – a visual query system for the ergonomic risk assessment of construction workers

Fan C, Mei Q, Wang X, Li X

arXiv preprint arXiv:2412.19954, 2024

3D pose estimation dataset and deep learning-based ergonomic risk assessment in construction

Fan C, Mei Q, Li X

Automation in Construction, vol. 164, pp. 105452, 2024

A computer vision framework for structural analysis of hand-drawn engineering sketches

Joffe I, Qian Y, Talebi-Kalaleh M, Mei Q

Sensors, vol. 24, no. 9, pp. 2923, 2024

Damage detection in bridge structures through compressed sensing of crowdsourced smartphone data

Talebi-Kalaleh M, Mei Q

Structural Control and Health Monitoring, vol. 2024, pp. 5436675, 2024

Capacity prediction and design optimization for laterally loaded monopiles in sandy soil using hybrid neural network and sequential quadratic programming method

Taherkhani A, Mei Q, Han F

Computers and Geotechnics, vol. 163, pp. 105745, 2023

Environment-aware worker trajectory prediction using surveillance camera in modular construction facilities

Yang Q, Mei Q, Fan C, Ma M, Li X

Buildings, vol. 13, no. 6, pp. 1502, 2023

A mobile sensing framework for bridge modal identification through an inverse problem solution procedure and moving-window time series models

Talebi-Kalaleh M, Mei Q

Sensors, vol. 23, no. 11, pp. 5154, 2023

A computer vision-based method to identify the international roughness index of highway pavements

Zeng J, Mei Q, Gül M

Journal of Infrastructure Intelligence and Resilience, vol. 1, no. 1, pp. 100004, 2022

Bridge mode shape identification using moving vehicles at traffic speeds through non-parametric sparse matrix completion

Mei Q, Shirzad‐Ghaleroudkhani N, Gül M, Ghahari F, Taciroglu E

Structural Control and Health Monitoring, vol. 28, no. 7, pp. e2747, 2021

A deep learning and computer vision based multi-player tracker for squash

Baclig MM, Ergezinger N, Mei Q, Gül M, Adeeb S, Westover L

Applied Sciences, vol. 10, no. 24, pp. 8793, 2020

Densely connected deep neural network considering connectivity of pixels for automatic crack detection

Mei Q, Gül M, Azim MR

Automation in Construction, vol. 110, pp. 103018, 2020

A cost effective solution for road crack inspection using cameras and deep neural networks

Mei Q, Gül M

Construction and Building Materials, vol. 156, pp. 119397, 2020

Multi-level feature fusion in densely connected deep learning architecture and depth first search for crack segmentation on images collected with smartphones

Mei Q, Gül M

Structural Health Monitoring, vol. 19, no. 6, pp. 1726-1744, 2020

Towards smart cities: crowdsensing-based monitoring of transportation infrastructure using moving vehicles

Mei Q, Gül M and Shirzad‐Ghaleroudkhani N

Journal of Civil Structural Health Monitoring, vol. 10, pp. 653-665, 2020

Frequency identification of bridges using smartphones on vehicles with variable features

Shirzad‐Ghaleroudkhani N, Mei Q, Gül M

Journal of Bridge Engineering, vol. 25, no. 7, pp. 04020041, 2020

Detection of suture needle using deep learning

Mei Q, Asgar-Deen D, Chainey J, Aalto D

Journal of Medical Robotics Research, vol. 4, no. 3, pp. 1942005, 2019

Indirect health monitoring of bridges using Mel-frequency cepstral coefficients and principal component analysis

Mei Q, Gül M, Boay M

Mechanical Systems and Signal Processing, vol. 119, pp. 523-546, 2019

A crowdsourcing-based methodology using smartphones for bridge health monitoring

Mei Q, Gül M

Structural Health Monitoring, vol. 18, no. 5-6, pp. 1602-1619, 2019

Damage assessment of shear-type structures under varying mass effects

Do NT, Mei Q, Gül M

Structural Monitoring and Maintenance, 6(3), 237-254. (, vol. 6, no. 3, pp. 237-254, 2019

Rapid and automated damage detection in buildings through ARMAX analysis of wind induced vibrations

Gislason GP, Mei Q, Gül M

Frontiers in Built Environment, vol. 5, pp. 16, 2019

A fixed-order time series model for damage detection and localization

Mei Q, Gül M

Journal of Civil Structural Health Monitoring, vol. 6, no. 5, pp. 763-777, 2016

Novel sensor clustering–based approach for simultaneous detection of stiffness and mass changes using output-only data

Mei Q, Gül M

Journal of Structural Engineering, vol. 141, no. 10, pp. 04014237, 2014