Artificial Intelligence (AI) in Project and Construction Management (PM/CM) Lab

AI-PMCM

É«ÖÐÉ« | Hung Family College of Engineering 
Artificial Intelligence (AI) in Project and Construction Management Lab for Research & Implementation 
Advancing Responsible AI Research, Practical Implementation

AI_PMCM_Lab_One_Page_Brochure.pdf

MISSION

The AI PM/CM Lab advances applied research and industry implementation of AI-enabled methods that improve planning, delivery, monitoring, risk management, safety, productivity, and decision support across project and construction management.

WHY THIS LAB

AI is rapidly changing how today's projects are planned, managed, delivered, and monitored. The Lab provides a É«ÖÐÉ« platform to bridge academic research and AI implementation with public agency needs.

CORE FOCUS AREAS

  • AI maturity assessment and implementation roadmaps
  • AI tools for scheduling, cost, documentation, risk, safety, claims, QA/QC, Asset Management and productivity
  • Digital delivery, project controls, and data-informed decision support
  • Responsible AI adoption, governance, and standards-informed implementation
  • Workforce development, training, and industry outreach

RESEARCH & IMPLEMENTATION ACTIVITIES

  • Applied research and proof-of-concept pilot projects
  • Industry workshops, short courses, and training materials
  • Evaluation of AI tools and PM/CM use cases
  • Implementation guides, checklists, and readiness assessments
  • Collaboration with public agencies, owners, consultants, contractors, and technology providers

STANDARDS-INFORMED OPPORTUNITY

The Lab builds upon É«ÖÐÉ« & Subject Matter Experts (SME) ongoing serving as a U.S. representative in ISO national and international efforts related to AI implementation standards for project, program, and portfolio management.

COLLABORATION OPPORTUNITIES

Industry and public-sector partners are invited to collaborate on applied research, pilot studies, workforce training, and AI implementation strategies for the built environment.

OUTCOMES

  • Practical AI implementation frameworks and roadmaps
  • Project controls and PM/CM workflow improvement tools
  • Case studies and lessons learned from industry pilots
  • Student research, capstone, and workforce development opportunities

CONTACT:

Dr. Elhami Nasr, Lab Director 
Professor | CM Graduate Advisor 
Hung Family College of Engineering | Civil Engineering & Construction Management 
California State University, Long Beach 
Office: VEC-308 | Email: elhami.nasr@csulb.edu | Phone: 909.331.2173