Team

Lab Director

Dr. Xinming (Sherry) Li

Associate Professor at the University of Alberta

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.

Research Team

Dedication. Expertise. Passion.

Our research team is composed of talented young researchers and engineers from diverse multidisciplinary backgrounds, including engineering, computer science, occupational health, and human factors. Together, we bring complementary expertise in sensing technologies, data analytics, ergonomics, and artificial intelligence to address complex challenges in human–technology interaction and workplace safety. The team fosters a collaborative environment that encourages innovation, cross-disciplinary learning, and the development of practical, real-world solutions.

Chao Fan

PhD Candidate

Chao specializes in the intersection of computer vision, deep learning, and ergonomic risk assessment within the construction industry. His work focuses on developing intelligent systems that analyze worker posture and physical demands using 3D pose estimation, vision-language models, and AI-driven automation. He has introduced novel datasets and skeletal models to enhance REBA and RULA evaluations, built interactive visual query systems for ergonomic risk identification, and applied predictive and generative AI to streamline Physical Demand Analysis. His research aims to improve safety, reduce injury risk, and bring scalable automation to traditionally manual assessment workflows.

Yuzhang Li

PhD Candidate

Yuzhang studies how motion and sensory distractions affect human fine motor control,
multitasking, and workload using eye-tracking, motion capture, IMUs, etc. This research
supports safer ergonomic and training designs for dynamic environments, such as warships,
aircraft, and ambulances.

Mohamed Assaf

PhD Candidate

Mohamed earned his Master of Science degree from the Hong Kong Polytechnic University. His past research experience includes using smart contracts and blockchain technology to enhance stakeholders’ cash flow in offsite construction projects. Currently, his research focuses on planning and managing activities in offsite construction projects through a combination of simulation, virtual reality, and digital twin tools. His research is expected to help offsite construction stakeholders make informed, collaborative decisions and develop a shared understanding of decision feasibility before and during project implementation.

Yuan Xiang

PhD Student

Xiang’s research focuses on applying Augmented Reality (AR) and Artificial Intelligence (AI) to improve human performance and safety in construction.Her work integrates computer vision, behavioral analytics, and human factors principles to enhance workers’ situational awareness, reduce cognitive load, and improve task performance in dynamic site environments. She is currently developing an AR task assistance system and guide the design of adaptive, data-driven training and safety management systems for Industry 5.0 construction.

Jiale Zhu

PhD Student

Jiale’s research integrates muscle activation and joint kinematics to strengthen automated ergonomic risk assessment. His work aims to make REBA/RULA more accurate and stable in continuous tasks by (1) analyzing how natural body sway affects scores and (2) developing data-driven ways to set scoring boundaries. The outcomes support more reliable and practical decision-making for worker safety in construction and similar settings.

Beixuan Dong

PhD Student

Beixuan specializes in infrastructure disaster management. Her recent research applies data-driven approaches to enhance disaster resilience in transportation networks, with a particular focus on impact assessment, prediction, and restoration. Her work aims to support the development of more adaptive and equitable infrastructure planning.

Weixin Image_20251023161041_9_563_edited

Zhihao Wei

PhD Student

Wei’s research focuses on developing intelligent and lightweight wearable systems that integrate deep learning, computer vision, and multimodal fusion to enhance human–machine interaction and safety in construction. His work explores online learning for adaptive gesture recognition, and applies structure optimization and CAE simulation to improve ergonomics and system performance. He aims to advance the development of personalized, data-driven, and real-time intelligent systems for next-generation construction and industrial applications.

Mohammad Alothman

PhD Student

Mohammad holds an MSc in Mechatronics Engineering. His current research quantifies and models sonographers’ workload in conventional and robot-assisted ultrasound, integrating ergonomics with AI and computer-vision analysis. The goal is to inform safer clinical ultrasound settings.

Yusen Jiao

PhD Student

Yusen is a Ph.D. student whose research focuses on LLM-based multi-agent systems for construction safety. His current work explores how AI agents can perform cross-sectional information extraction to understand and answer complex safety-related questions more effectively. By integrating graph structures and multi-agent collaboration mechanisms, his study aims to develop context-aware conversational assistants that enhance safety knowledge management and decision-making in construction environments.

Xiaoying Zhang

PhD Student

Xiaoying Zhang’s research focuses on automating pre-construction site hazard assessment. Her work integrates hazard dataset development, object-detection-based recognition models, and AR applications into a unified framework to enhance risk identification and safety management during the pre-construction phase.

Leyi Zhou

MSc Student

Leyi developes Lean-based Standard Operating Procedures to support the productive and safe operation.

Congzhou Yuan

MSc Student

Congzhou's work advances real-time, sensor-fused ergonomics and biomechanics. I build real-time pipelines that combine IMU motion capture (Xsens), surface EMG (Delsys), and heart rate to estimate posture load, detect muscle fatigue, and deliver live feedback for construction and sports.

Muhammad Afnan Khan

MSc Student

Muhammad’s research focuses on developing immersive and interactive learning environments that integrate Virtual Reality (VR) and robotics for engineering education and workforce training. His work aims to enhance accessibility and engagement in robotics education through simulation-based, project-oriented learning methods. He is currently developing a VR-based robotics training platform using the Dobot CR5 collaborative robot to teach fundamental concepts of robot kinematics, control, and operation in an interactive, risk-free environment. His research also explores the application of digital twins and human–robot interaction to bridge virtual learning with real-world robotic systems.

Staff

Dr. Yiding Sun

Post-doctoral Fellow

Yiding’s research develops an intelligent integration framework to advance digital transformation in small and medium-sized enterprises (SMEs). Her RAIP and RAIP-AI platforms enable seamless data synchronization, interoperability, and semantic querying across enterprise systems. She also integrates this framework with digital product design and manufacturing, enhancing efficiency and customization in SME operations.

Samuel Iwuchukwu

Software Engineer

Samuel's research focuses on integrating system silos in prefabrication construction through a service broker architecture. Using a collaborative industry partner as a case study, the project maps existing data systems, identifies key workflows, and develops microservices across major management areas. The goal is to unify these modules via a service broker framework to enhance operational efficiency.

Former Graduate Students

Former students have pursued diverse careers in academia, data analytics, artificial intelligence, and project management etc. This range of career paths reflects the strong technical, organizational, and interpersonal competencies—as well as the commitment to diversity—that they develop and carry forward throughout their professional journeys.

Dr. Qiuling Yang

Dr. Yang’s research focused on computer vision, reinforcement learning, and optimization for construction safety. Her project develops data-driven models that integrate real-time motion and environmental data with injury reports to predict safety hazards. Using AI-based computer vision, the system automatically identifies risks in real time to support safer and more efficient construction operations.

Current position: AI Scientist at IQVIA

Dr. Jingwen (Karen) Wang

Jingwen’s research interests included 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.

Current Position: Assistant Professor at the Guangzhou University

Dr. Regina Celi Dias Ferreira Barkokébas

Regina conducted analytical and experimental research to develop a VR–motion capture–based ergonomic risk assessment method for improving workplace ergonomics in construction manufacturing. She created a flexible VR simulation approach for ergonomic analysis and safety training, enabling proactive identification and mitigation of risks during workstation design and task training.

Current Position: Assistant Professor at the Pontificia Universidad Católica de Chile

Dr. Yuxuan (Sherie) Zhang

Sherie’s research focused on user-centered design for residential environments. She developed an integrated framework combining knowledge-based systems and immersive virtual reality to link human experience with architectural features. Using both qualitative and quantitative data, the study helps designers uncover tacit user needs and provides guidelines to enhance occupant experience.

Current Position: Associate Professor at the Nanjing University of Aeronautics and Astronautics

Dr. Aswin Ramaswamy Govindan

Aswin’s research focused on developing a rapid and robust Fuzzy Expert System for ergonomic risk assessment in construction manufacturing. The system uses fuzzy if–then rules based on physical, environmental, and sensory factors to streamline decision-making, reduce assessment time, and support data-driven ergonomic improvements in the workplace.

Current Position: Data Scientist at Fiddlehead Technology

Dr. Shuzhi Xu

Shuzhi's research interests included 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.

Current Position: Research Fellow at the University of Osaka

Jiahuan Chen

Jiahuan's research project was 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.

Current Position: To be added

Changcui (Kim) Qiu

Her research topic was occupational safety hazard analysis and control to support enterprise health and safety information digital transformation.

Current Position: To be added

Lindsey Agnew

Lindsey's research focused on exploring the effect of torso mass in direct head impacts using a Hybrid III neck and a novel surrogate neck model.

Current Position: To be added

Ramin Aliasgari

Ramin's research focused on automating motion capture and AI based physical demand analysis.

Current Position: Project Management Coordinator at AECOM company

Mohammed Al-Duais

Mohammed's research focused 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.

Current Position: Project Management Coordinator at AECOM company

Lab Director

Research Team

Yuzhang studies how motion and sensory distractions affect human fine motor control, multitasking, and workload using eye-tracking, motion capture, IMUs, etc. This research supports safer ergonomic and training designs for dynamic environments, such as warships, aircraft, and ambulances.

Mohammad holds an MSc in Mechatronics Engineering. His current research quantifies and models sonographers’ workload in conventional and robot-assisted ultrasound, integrating ergonomics with AI and computer-vision analysis. The goal is to inform safer clinical ultrasound settings.

Leyi developes Lean-based Standard Operating Procedures to support the productive and safe operation.

Congzhou's work advances real-time, sensor-fused ergonomics and biomechanics. I build real-time pipelines that combine IMU motion capture (Xsens), surface EMG (Delsys), and heart rate to estimate posture load, detect muscle fatigue, and deliver live feedback for construction and sports.

Staff

Former Graduate Students

Jiahuan's research project was 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.

Her research topic was occupational safety hazard analysis and control to support enterprise health and safety information digital transformation.

Lindsey's research focused on exploring the effect of torso mass in direct head impacts using a Hybrid III neck and a novel surrogate neck model.

Ramin's research focused on automating motion capture and AI based physical demand analysis.

Yuzhang studies how motion and sensory distractions affect human fine motor control,
multitasking, and workload using eye-tracking, motion capture, IMUs, etc. This research
supports safer ergonomic and training designs for dynamic environments, such as warships,
aircraft, and ambulances.