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.
Aswin Ramaswamy Govindan
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.
Shuzhi's research interests include the design for additive manufacturing, topology optimization, and high-performance computation. His thesis topic, 'topology optimization considering the additive manufacturing process constraints', aims to promote the application of topology optimization technology in the design and manufacturing of larger-scale products.
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.
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.
Zhihao’s project is to develop a flexible manipulator design algorithm based on topology optimization. Topology optimization is a mathematical method to optimize the material distribution to design a better performance structure. He is developing geometrically nonlinear and hyperelastic topology optimization algorithm to describe large deformation structural behavior, using multiple materials and well-arranging them to realize the flexibility of manipulator. By using stress constraints and displacement constraints, the structure failure and damage can be simulated and predicted. He will use additive and subtractive manufacturing technology to verify the effectiveness and manufacturability of manipulator design.
Xiang received her Master of Science in Digital Engineering Management from University College London. Her previous research directions include Digital Twin platform development, data-integrated solutions improving project performance, and applying Smart Contracts in infrastructure procurement. She is pursuing a Doctor of Philosophy in Engineering Management. Her current research mainly focuses on using Augmented Reality in the construction industry. The project is expected to develop a data-enabled skill training and safety-conscious enhanced platform from the practical meaning. And it will contribute to the theory development for safety management and worker-oriented engineering management utilizing computer vision and artificial intelligence.
Mohamed’s research tackles the enhancement of the offsite construction (OSC) implementation. It uses advanced visualization technologies, such as virtual reality (VR), and
biometric sensing, such as eye trackers and electroencephalogram (EEG). The main areas of
interest in Mohamed’s research include crane layout planning, workers' training, and
Jiale’s research is about body sway analysis. There are some minor movements of body joints during continuous motions due to body sway occurs naturally, which will cause extra risk scores. His project investigates the body sway influences on the automated ergonomic risk assessments in an optical marked-based motion capture system. Ergonomic risk assessment incorporated body sway analysis method could help to eliminate the issues of overestimations and fluctuations.
Leyi graduated from University of Alberta in 2021 from Mechanical Engineering. His research project focuses on risk assessment in industrial environment using virtual reality and motion capture systems. The VR systems simulate the actual working environment and the motion capture systems analyze the force and stress in human body. His proposal is to develop the systems to estimate the risk, and provide visualized training to reduce the proteins of body injury from improper movements at workstations.
Mohammed's research focuses on leveraging computer vision techniques to improve worker safety. Specifically, he aims to develop innovative machine learning algorithms that can detect and mitigate potential hazards in the workplace, utilizing his interdisciplinary background in civil engineering and programming to create a safer environment for workers.
Dr. Qiuling Yang
Former Post-doctoral Fellow
Dr. Yang's research in our lab includes computer vision with application to construction safety, reinforcement learning, and optimization. Her project aims 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 is able to automatically identify risks in real-time to support decision making in safety hazard control and productivity improvement.
Dr. Jingwen (Karen) Wang
Former PhD Student, currently an Assistant Professor at the Guangzhou University
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.
Dr. Regina Celi Dias Ferreira Barkokébas
Former PhD Student, currently an Assistant Professor at the Pontificia Universidad Católica de Chile
Regina conducted 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 developed a novel, flexible VR-based simulation approach for robust ergonomic analysis and safety training 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. Proactive trainings can be approached as well to prevent the potential risks and injuries.
Dr. Yuxuan (Sherie) Zhang
Former PhD Student, currently an Assistant Professor at the Nanjing University of Aeronautics and Astronautics
Sherie had 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.
Former 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.
Former MSc Student, currently a project management coordinator in AECOM
Ramin works on automating motion capture and AI based physical demand analysis.
Former MSc student
Her research topic was occupational safety hazard analysis and control to support enterprise health and safety information digital transformation.
Former MSc Student
Lindsey's research focuses on exploring the effect of torso mass in direct head impacts using a Hybrid III neck and a novel surrogate neck model.