top of page

Journal Papers (Trainees are underlined)

21. Fan C, Mei Q and Li X (2024) "3D pose estimation dataset and deep learning-based ergonomic risk assessment in construction." Automation in Construction, 164, 105452. (PDF)

20. Joffe I, Qian Y, Talebi-Kalaleh M and Mei Q (2024) "A computer vision framework for structural analysis of hand-drawn engineering sketches." Sensors, 24(9), 2923. (PDF)

19. Talebi-Kalaleh M, and Mei Q (2024) "Damage detection in bridge structures through compressed sensing of crowdsourced smartphone data." Structural Control and Health Monitoring, 2024, 5436675. (PDF)

18. Taherkhani A, Mei Q and Han F (2023) "Capacity prediction and design optimization for laterally loaded monopiles in sandy soil using hybrid neural network and sequential quadratic programming method." Computers and Geotechnics, 163, 105745. (PDF)

17. Yang Q, Mei Q, Fan C, Ma M and Li X (2023) "Environment-aware worker trajectory prediction using surveillance camera in modular construction facilities." Buildings, 13(6), 1502. (PDF)

16. Talebi-Kalaleh M, and Mei Q (2023) "A mobile sensing framework for bridge modal identification through an inverse problem solution procedure and moving-window time series models." Sensors, 23(11), 5154. (PDF)

15. Zeng J, Mei Q and Gül M (2022) "A computer vision-based method to identify the international roughness index of highway pavements." Journal of Infrastructure Intelligence and Resilience, 1(1), 100004. (PDF)

14. Mei Q, Shirzad‐Ghaleroudkhani N, Gül M, Ghahari F and Taciroglu E (2021) "Bridge mode shape identification using moving vehicles at traffic speeds through non-parametric sparse matrix completion." Structural Control and Health Monitoring, 28(7), e2747. (PDF)

13. Baclig MMErgezinger N, Mei Q, Gül M, Adeeb S and Westover L (2020) "A deep learning and computer vision based multi-player tracker for squash." Applied Sciences, 10(24), pp.8793. (PDF)

12. Mei Q, Gül M and Azim MR (2020) "Densely connected deep neural network considering connectivity of pixels for automatic crack detection." Automation in Construction, 110, pp.103018. (PDF)

11. Mei Q, and Gül M (2020) "A cost effective solution for road crack inspection using cameras and deep neural networks." Construction and Building Materials, 156, pp.119397. (PDF)

10. Mei Q, and Gül M (2020) "Multi-level feature fusion in densely connected deep learning architecture and depth first search for crack segmentation on images collected with smartphones." Structural Health Monitoring, pp.1475921719896813. (PDF)

9. Mei Q, Gül M and Shirzad‐Ghaleroudkhani N (2020) "Towards smart cities: crowdsensing-based monitoring of transportation infrastructure using moving vehicles." Journal of Civil Structural Health Monitoring, 10, pp. 653–665. (PDF)

8. Mei Q, Asgar-Deen D, Chainey J and Aalto D (2020) “Detection of suture needle using deep learning.” Journal of Medical Robotics Research, pp.1-9.

7. Shirzad‐Ghaleroudkhani NMei Q, and Gül M (2020) "Frequency identification of bridges using smartphones on vehicles with variable features." Journal of Bridge Engineering, 25(7), pp. 04020041. (PDF)

6. Mei Q, Gül M and Boay M (2019) "Indirect health monitoring of bridges using Mel-frequency cepstral coefficients and principal component analysis." Mechanical Systems and Signal Processing, 119, pp.523-546. (PDF)

5. Mei Q, and Gül M (2019) "A crowdsourcing-based methodology using smartphones for bridge health monitoring." Structural Health Monitoring, 18(5-6), pp.1602-1619. (PDF)

4. Do NT, Mei Q, and Gül M (2019) "Damage assessment of shear-type structures under varying mass effects." Structural Monitoring and Maintenance, 6(3), pp.237-254. (PDF)

3. Gislason GPMei Q, and Gül M (2019) "Rapid and automated damage detection in buildings through ARMAX analysis of wind induced vibrations." Frontiers in Built Environment, 5(16). (PDF)

2. Mei Q, and Gül M (2016) "A fixed-order time series model for damage detection and localization." Journal of Civil Structural Health Monitoring, 6(5), pp.763-777. (PDF)

1. Mei Q, and Gül M (2014) "Novel sensor clustering–based approach for simultaneous detection of stiffness and mass changes using output-only data." Journal of Structural Engineering, 141(10), pp.04014237. (PDF)

Book Chapters (Trainees are underlined)

1. Shirzad-Ghaleroudkhani N, Mei, Q and Gül M (2022) "A crowdsensing-based platform for transportation infrastructure monitoring and management in smart cities." In The Rise of Smart Cities (pp. 609-624). Butterworth-Heinemann. (PDF)

Conference Papers (Trainees are underlined)

24. Talebi-Kalaleh M and Mei Q (2024) "Toward indirect real-time prediction of bridge vibration responses under traffic flow through a population of connected sensing vehicles." Engineering Mechanics Institute Conference and Probabilistic Mechanics & Reliability Conference (EMI/PMC)May 28-31, Chicago, IL, USA.

23. Wang ZSabek M, Wu Y, Mei Q, Lee G and Gonzalez V (2024) "Digital twin based integrated decision support system for enhanced decision-making in the last planner system." the 32nd International Group for Lean Construction Conference (IGLC32), July 1-7, Auckland, New Zealand.

22. Sarothi SZ, Chui YH and Mei Q (2024) "A reinforcement learning approach for structural design optimization of glulam beam." Canadian Society for Civil Engineering (CSCE) Annual Conference, June 5-7, Niagara, ON, Canada.

21. Xie H, Mei Q, Chui YH and Yu H (2024) "Comparison of prefabricated building project designs based on analysis of floor plan drawings using deep learning." Canadian Society for Civil Engineering (CSCE) Annual Conference, June 5-7, Niagara, ON, Canada.

20. Sabek M, Gonzalez V, Mei Q and Lee G (2024) "Enhancing construction site safety and efficiency with YOLO v8-based computer vision model." Canadian Society for Civil Engineering (CSCE) Annual Conference, June 5-7, Niagara, ON, Canada.

19. Ji B, Mei Q, Taraghi P and Adeeb S (2024) "Neural network for constitutive modelling of beam structures." Pressure Vessels & Piping Conference (PVP), July 28-August 2, Bellevue, WA, USA.

18Fan C, Mei Q, and Li X (2024) "Assisting in the identification of ergonomic risks for workers: a large vision-language model approach." 41st International Symposium on Automation and Robotics in Construction (ISARC), June 3-5, Lille, France.

17. Alduais M, Taherkhani A, Mei Q and Han F (2024) "Prediction for lateral response of monopiles: deep learning model on small datasets using transfer learning." Geo-Congress, February 25-28, Vancouver, BC, Canada.

16. Yuan X, Mei Q and Li X (2023) “Integrating real-time object detection into an AR-driven task assistance prototype: an approach towards reducing specific motions in therbligs.” the 23rd International Conference on Construction Applications of Virtual Reality (CONVR), November 13-15, Florence, Italy.

15. Talebi-Kalaleh M and Mei Q (2023) “A novel drive-by system identification approach for bridges utilizing a modal FRF similarity criterion and soft-imputing” 10th International Conference on Experimental Vibration Analysis for Civil Engineering Structures (EVACES), August 30-September 1, Milan, Italy.

14. Yuan X, Mei Q and Li X (2023) “Augmented reality-based vocational training for the construction workforce: prototype development and experiment design.” Canadian Society for Civil Engineering (CSCE) Annual Conference, May 24-27, Moncton, NB, Canada.

13. Fan C, Mei Q and Li X (2023) “Real-time ergonomic risk assessment approach for construction workers based on computer vision.” Canadian Society for Civil Engineering (CSCE) Annual Conference, May 24-27, Moncton, NB, Canada.

12. Zeng J, Mei Q and Gül M (2023) “Bridge damage detection using passing-by vehicles and CNN-LSTM autoencoder.” Canadian Society for Civil Engineering (CSCE) Annual Conference, May 24-27, Moncton, NB, Canada.

11. Fan C, Mei Q, Yang Q and Li X (2022) “Computer-vision based rapid entire body analysis (REBA) estimation.” Modular and Offsite Construction Summit, July 27-29, Edmonton, AB, Canada.

10. Yang Q, Mei Q, Fan C, Ma M and Li X (2022) “Environment-aware worker trajectory prediction using surveillance camera on modular construction sites.” Modular and Offsite Construction Summit, July 27-29, Edmonton, AB, Canada.

9. Mei Q (2022) “The application of compressed sensing on crowdsensing-based indirect bridge condition monitoring.” Canadian Society for Civil Engineering (CSCE) Annual Conference, May 25-28, Whistler, BC, Canada.

8. Mei Q, and Gül M (2019) “Monitoring a population of bridges in smart cities using smartphones.” Structures Congress 2019, April 24–27, Orlando, FL, United States.

7. Mei Q, and Gül M (2018) “A novel indirect damage assessment method for short and medium span bridges,” 10th International Conference on Short and Medium Span Bridges (SMSB 2018), July 31-August 3, Quebec City, Quebec, Canada.

6. Mei Q, and Gul M (2014) “Damage assessment of a 4-span bridge type structure using time series analysis.” Istanbul Bridge Conference, August 11-13, Istanbul, Turkey. 

5. Mei Q, and Gül M (2014) “Experimental study for a time series based method for damage detection using output data only,” 9th International Conference on Short and Medium Span Bridges (SMSB 2014), July 15-18, Calgary, AB, Canada.

4. Mei Q, and Gül M (2014) “Application of a novel time series based method for damage detection, localization and quantification using output only acceleration data.” 7th International Conference on Bridge Maintenance, Safety, and Management (IABMAS 2014), Jul. 7-11, Shanghai, China. 

3. Mei Q, and Gül M (2013) “Anomaly detection using a novel time series approach: application to the ASCE benchmark problem.” The 6th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-6), December 9-11, Hong Kong, China. 

2. Mei Q, and Gül M (2013) "Detection, localization and quantification of anomalies in mass, stiffness and damping based on time series modelling using output-only data. " A Roadmap to Intelligent Structures: Proceedings of the Ninth International Workshop on Structural Health Monitoring (IWHSM 2013), Volume 4. DEStech Publications Lancaster, 112-119. 

1. Mei Q, and Gül M (2013) "An improved methodology for anomaly detection based on time series modeling." Topics in Dynamics of Civil Structures: Proceedings of 31th International Modal Analysis Conference (IMAC XXXI), Volume 4. Springer New York, 277-281. 

bottom of page