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UOK

PhD in Robotics and AI for Construction Safety and Worker Performance

University of Kansas Department of Civil, Environmental & Architectural Engineering
Self-funded 🎓 Artificial Intelligence 🎓 Civil Engineering 🎓 Robotics digital twin robotics artificial intelligence virtual reality construction safety human-robot interaction construction automation safety analytics

Explore robotics and AI to transform construction safety and worker performance. Develop systems that enable intelligent automation and immersive training, addressing critical safety challenges on construction sites.

AI-generated overview

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Why This Research Matters

This research tackles significant safety risks in the construction industry by leveraging AI and robotics to reduce accidents and improve worker health. It advances technology that makes construction sites safer and more efficient, aiding real-world construction and training practices with cutting-edge, human-centered tools.

Construction Robotics Construction Automation Human Robot Collaboration VR/AR Technologies

Project Description

Project Overview

This research focuses on advancing construction safety and enhancing worker performance through intelligent robotics, artificial intelligence, and human-centered sensing systems. The work spans automation in construction tasks, AI-powered safety analytics, dynamic human-robot interaction, and immersive technologies such as virtual reality and digital twins for training and decision support.

What You Will Do

You will develop robotic solutions for construction automation and site monitoring, design AI models for safety risk assessment, investigate human-robot collaboration in complex environments, and create virtual reality systems to improve training. The work integrates interdisciplinary knowledge from AI, robotics, and construction engineering.

Expected Outcomes

Expected results include novel AI and robotic frameworks improving construction site safety, new metrics for worker performance, validated human-robot operation models, and advanced virtual training platforms. This research aims to publish in top journals and equip students with interdisciplinary expertise.

Why This Matters

Construction remains a high-risk industry with significant safety challenges. Integrating cutting-edge robotics and AI can reduce accidents, improve worker health and efficiency, and transform construction practices to be more responsive and human-centered.

Entry Requirements

Candidates should have degrees related to Mechanical Engineering, Electrical Engineering, Computer Science, Civil Engineering, Construction Engineering and Management, or related disciplines. Motivation for interdisciplinary work, interest in AI/ML, experience with robot control, path planning, human-robot interaction, and skills in Python, MATLAB, ROS or simulation tools are preferred.

How to Apply

Interested applicants should fill out the form at https://forms.gle/fctvqVFNiBWqe9xy9. The supervisor will contact candidates whose profiles match well.

Eligibility

UK/Home
EU
International

Supervisor Profile

DA
Dr. Amit Ojha
University of Kansas, Department of Civil, Environmental & Architectural Engineering
660 Citations
14 h-index
Google Scholar

Dr. Amit Ojha, joining the University of Kansas as an Assistant Professor, researches intelligent automation in construction with a focus on robotics, human-robot collaboration, and AI. His work integrates immersive technologies and physiological sensing to enhance construction safety and worker performance. He has published widely in top journals and emphasizes mentoring students in research and publication.

Key Publications

2021 127 citations
Assessing occupational risk of heat stress at construction: A worker-centric wearable sensor-based approach
2023 108 citations
Human-robot teaming in construction: Evaluative safety training through the integration of immersive technologies and wearable physiological sensing
2022 54 citations
Workers’ trust in collaborative construction robots: EEG-based trust recognition in an immersive environment
2020 45 citations
Construction Safety Training Methods and their Evaluation Approaches: A Systematic Literature Review
2024 33 citations
Physiological impact of powered back-support exoskeletons in construction: Analyzing muscle fatigue, metabolic cost, ergonomic risks, and stability

Research Contributions

Developed wearable sensor-based approaches to assess occupational heat stress risks for construction workers.
Enables improved worker safety and health monitoring through personalized sensing technologies.
Integrated immersive technologies and wearable physiological sensing to enhance human-robot teaming and safety training in construction.
Improved training efficacy and safety outcomes in construction environments involving robotics.
Advanced understanding of workers' trust in collaborative robots using EEG-based trust recognition in immersive environments.
Supports development of more effective and accepted robotic systems in human-robot collaborative work settings.
Analyzed the physiological effects of powered back-support exoskeletons on muscle fatigue, metabolic cost, ergonomic risks, and stability for construction workers.
Informs design and implementation of wearable exoskeletons to reduce physical strain and injury risk on the job.

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