Lab Members


Xinming Li


Dr. Xinming Li's research seeks improvements in industrialized construction by evaluating ergonomic risks and investigating corresponding corrective measures to secure the health and safety of workers and enhance workplace productivity.
Her areas of focus include physical demand analysis, human body physiological measurement, ergonomic risk assessment based on 3D visualization modelling of operational tasks, and lean manufacturing in industrialized construction. She has been developing a comprehensive post-3D visualization “ErgoSystem” that automates ergonomic risk assessment based on 3D modelling with the support of a user-friendly platform for rapid workplace design. Her research targets improved work performance and workplace design, ensuring a healthy working environment. The outcomes of her research help industry collaborators to reduce workplace injuries and claims, develop robust return-to-work programs, reduce workers’ compensation premiums, and improve productivity.
Dr. Li’s other research interests include sustainable building systems, renewable energy sources, and smart system control. In previous research she developed post-design heating system control to increase the efficiency and minimize the operational cost of a residential space heating system integrating renewable energy sources.
Throughout her research activities, she has worked closely with industry, and her work has yielded results which have benefited construction manufacturing and building management enterprises in tangible ways. As a result, she has not only developed academic contributions, but also has provided recommendations that have helped to improve the competitive edge of industry collaborators.


Qiuling Yang

Post-Doctoral Fellow

Qiuling’s research interests include computer vision with application to construction safety, reinforcement learning, and optimization. Her currently project is aiming to develop data-driven safety hazard prediction modelling by integrating real-time physical motion and environment detection with injury reports in construction site. Based on computer vision and artificial intelligence techniques, the model will be able to automatically identify risks in real-time to support decision making in safety hazard control and productivity improvement.


Regina Celi Dias Ferreira Barkokébas

PhD Candidate

Regina is conducting extensive analytical and experimental research toward the development of a VR-motion capture-based ergonomic risk assessment method to improve workplace ergonomics in construction manufacturing facilities. She is developing a novel, flexible VR-based simulation approach for robust ergonomic analysis that can be applied from the workstation design development phase through to task training based on actual motion data. By integrating VR with motion capture, the body motions involved in undertaking a task can be simulated and anticipated in a laboratory setting such that ergonomic risks can be identified and mitigated proactively at the workstation design stage.


Jingwen (Karen) Wang

PhD Candidate

Jingwen’s research interests include human body physiological measurement, fuzzy logic-based automated ergonomic risk analysis in 3D visualization, workplace productivity enhancement, and corrective measures for rapid ergonomic-centric workplace design in industrialized construction. Her research targets improved work performance and workplace design, ensuring enhanced productivity in a healthy working environment.


Yuxuan (Sherie) Zhang

PhD Student

Sherie has been focusing on promoting user-centred design for residential environments. The work attempts to provide an integrated framework that incorporates knowledge-based systems and immersive virtual reality to explore and associate the human experience with architectural design features. Data collected in qualitative and quantitive manners to support and framework and maintain validity and reliability. This research assists the designer in expliciting the tacit user requirements and can be referred to as the designer's guidelines when conducting the designer tasks to improve occupants’ experiences.

Chao Fan.JPG

Chao Fan

PhD student

Chao's study will leverage commercial-grade security cameras that have been widely installed in construction workplaces by developing methods that can automatically extract 3D human body movements from a long-range video. The method will be developed based on deep convolutional neural networks, and a large amount of real-life video data under different working conditions will be collected and labelled for model training purposes.


Yuzhang Li

PhD student

Aviation is a highly developed field and flying is one of the safest way to travel. However, human related operational error is still one of the major causes of aviation accidents. A better human-system interaction, including cognitive engineering, human factors, and ergonomics, is critical to enhance aviation safety. Eye-tracking technology enables users to explore what pilots are looking at, which provide valuable information to observe their behaviors. Yuzhang's research involves the use of eye-tracking devices, flight simulators, and non-immersive heart-rate detectors to analyze pilots’ behaviors when pilots conduct multitasking (flying, navigating, and communicating with controls). Trainings will be proposed to improve the ability of multitasking.


Jiahuan Chen

MSc student

Jiahuan's research project is the prediction of the upper limb posture for reaching tasks. This project will benefit many areas, such as product design (virtually testing products), ergonomic workplace design and computer graphics. He is currently focusing on the reaching task when the fingertip reaches target points. A program has been developed in Matlab, where a Denavit-Hartenberg model is established for male adults. Since the upper limb is a redundant system, an optimization module is merged into this program, and a bi-criterion objective function is also proposed for this optimization module.


Changcui (Kim) Qiu

MSc student

Kim received her Bachelor of Science in 2020 in electrical engineering from University of Alberta. She is currently pursuing a master’s degree in engineering management at University of Alberta. She got involved in the project that relates to a blended analysis of occupational safety hazards and risk assessment using data mining approach and quantitative evaluation. Her current research topic focuses on building an enterprise digital twin for panelized building manufacture that connects ERP, structure design software, budget estimation, inventory and logistics management, production plan and control with the concept of Industry 4.0 and real-time digital reproduction from the physical entities.


Aswin Ramaswamy Govindan

MSc student

Aswin's research project is to develop a rapid and robust Fuzzy Expert System for conducting ergonomic risk assessments to improve workplace ergonomics in construction manufacturing facilities. This study aims to ease the decision-making process required for administrative and engineering controls using a collection of fuzzy if-then rules based on physical, environmental and sensory ergonomics. The proposed system reduces the non-value-added time in conducting risk assessments and allows managers/ergonomists to concentrate on strategic implementation of ergonomic improvements in the workplace for the quantified data collected from humans and other workplace elements.


Lindsey Agnew

MSc student

Lindsey's research focus is head and neck injury biomechanics. Her project investigates head and neck kinematic and kinetic responses to indirect loading using instrumented surrogate models and an impact pendulum experiment. This project aims to demonstrate the biofidelity of a novel surrogate neck compared to human volunteer sled test data. This would allow for standardization of testing and injury assessment to further understand and safeguard against head injury.