Ebenezer Olukanni

Virginia Tech

Papers

1

Total Citations

2

H-Index

1

About

Dr. Ebenezer Olukanni is a forward-thinking researcher at the intersection of construction education, human–robot collaboration (HRC), and artificial intelligence. His work explores how emerging technologies—particularly multimodal large language models (LLMs)—can transform training paradigms for the construction workforce. In his landmark narrative review, Olukanni critically examines the integration of LLMs into construction curricula to prepare students for collaborative robotics environments, addressing industry-wide challenges such as skilled labor shortages and safety risks. This pioneering synthesis has already garnered early citations, signaling its growing influence. Beyond this, Olukanni’s broader contributions focus on bridging the gap between advanced AI systems and practical, human-centered learning in high-stakes industrial settings. By advocating for interdisciplinary approaches that merge pedagogy, robotics, and natural language processing, he is shaping how future engineers and construction professionals will interact with intelligent machines. His work stands out for its timely relevance, as industries worldwide scramble to upskill workforces for an automated future. Olukanni’s research not only advances academic discourse but also offers actionable frameworks for educators and policymakers navigating the Fourth Industrial Revolution.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Multimodal Large Language Models in Construction Education for Learning Human–Robot Collaboration: A Narrative Review
2 citations · 2026
📈 Most Prolific Year: 2026 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: Virginia Tech

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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