Doctoral Students Advised as Chair/Co-Chair

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Abdullahi Ibrahim

Construction Workers' Situational Awareness: Investigating Physical Fatigue and Emerging Technologies (Graduated Summer 2024)

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Ifeanyi Okpala

Robotics and Automation in Construction: Developing Foundational Insight and Tools to Support Safe Implementation (Graduated Spring 2022)

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Muhammad Khan

Developing Tools for Preventing Falls from Roof* (Fall 2025)

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Muhammad Sharjeel Anjum

Muhammad Sharjeel Anjum's research focuses exclusively on worker safety and health, utilizing cutting-edge technology that combines computer science with machine learning and virtual reality. His work integrates a medical perspective on fatigue identification through theoretical modeling and machine learning methods to identify both central and physical fatigue. He has a versatile educational background, with an undergraduate degree in computer science and a master’s in construction and building

Image of Olugbenro Ogunrinde
Olugbenro Ogunrinde

Enhancing Highway Quality Management using Emerging Methods. (Graduated Spring 2020)

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Prosper Gbiengu

Prosper Gbiengu’s research focuses on advancing both fundamental knowledge and practical applications of wearable robotic technology to improve health and safety in the construction industry. His research emphasizes the development, implementation, and adaptation of wearable robots designed to support workers’ physical tasks, reduce fatigue, and mitigate potential hazards. By integrating engineering principles, ergonomics, and human-computer interaction, his research aims to create wearable solu

Master Students Advised as Chair/Co-Chair

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Abdallah Abdallah

Enhancing Electrical Utility Work Zone Safety Using Intrusion Alert Systems (Fall 2023)

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Seoyoung Cheon

Examining the Influence of Robot-supported Operation on Hazard Identification in Virtual Reality (Fall 2024).

Externships

Image of Chidozie Managwu
Chidozie Managwu

Machine Learning Engineer