Behzad Esmaeili
Purdue University, IN·Engineering
People with attention-deficit/hyperactivity disorder (ADHD) make up about 4.2% of workers. They are often pushed out of construction jobs because of concern that they face higher injury risk.
- Fields
Engineering
Computer Science
Psychology
- Topics
construction safety
human-AI teaming
worker-AI teaming
- Grants
- 1 known grant, last ended Sep 2026
What they work on
- Build an AI-driven learning platform that turns non-invasive biomechanical and neuro-psychophysiological signals from construction workers into models that predict their behavior, enabling personalized worker-AI teaming.
- Investigate risk-taking behavior and cognitive processes of construction workers with attention-deficit/hyperactivity disorder (ADHD), to inform how AI teammates should assess and respond to them.
- Identify barriers to construction workers adopting AI and wearable technologies, and study unintended consequences of worker-AI teaming, including technological over-reliance and privacy threats.
- Assess the socioeconomic impacts of improved access to construction jobs for workers diagnosed with ADHD in the context of human-AI partnerships.
More about the research
This project asks whether AI-driven helpers, including collaborative robots ('co-bots'), could act as true teammates. Such teammates would sense how a worker is doing, adapt, and support both safety and the worker's strengths. For that to work, machines must predict workers' behavior and workers must be able to engage them as partners, not only tools.
Why it matters
ADHD is linked to more than 120 million lost workdays a year in the U.S., a human capital value of about $19.5 billion. AI teammates that predict and support worker behavior could widen access to construction jobs for people with ADHD while improving job-site safety. The findings on human-machine teaming could also guide how such tools are introduced on job sites and in other industries.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Jingang Yi
Rutgers University-New Brunswick, NJ·Engineering
Develop machine learning methods for real-time recognition of construction workers' activities and estimation of their body posture, using wearable sensors.
Sampath Jayarathna
Old Dominion University, VA·Computer Science·Early-career
Build a "streaming hub," a framework for real-time, computationally efficient processing of eye-tracking data from one or more users, in place of offline batch analysis.
Lap Fai Yu
George Mason University, VA·Computer Science
Investigate how artificial intelligence techniques can be integrated with mixed reality headsets to assist first responders during tasks such as firefighting and search and rescue.
The school
Purdue University: 43 labs on PI Pages, $932M a year on research, 833 research doctorates a year.
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