Problem
Construction information is fragmented across BIM, schedules, documents, imagery and project-control records.
CIVIL ENGINEERING × DIGITAL CONSTRUCTION × AI
I'm Mohammad Zia Bakhteyari — a Civil Engineer, Urban Planner and Full-Stack Software Engineer developing toward doctoral research in Construction Informatics.
An interdisciplinary engineering profile
Civil Engineering → Urban Planning → Software Engineering → Applied AI → Construction Informatics.
My work sits at the intersection of engineering knowledge and computational systems. I am particularly interested in transforming BIM models, schedules, site observations and project documents into useful, interpretable decision support for construction and infrastructure management.
Prospective doctoral researcher
Integrating digital project information for predictive decision support.
Construction information is fragmented across BIM, schedules, documents, imagery and project-control records.
How can heterogeneous project information become reliable, interpretable intelligence for real management workflows?
Workflow analysis, data architecture, computer vision, ML, NLP, multimodal models and optimisation.
AI should support professional judgement while keeping managerial responsibility explicit.
Engineering + AI + software
ETABS · SAFE · AutoCAD
Computer Vision · TensorFlow/Keras · UAV concept
CNN · OpenCV · TensorFlow/Keras
React · Redux · Rails · JWT
Selected experience
Supervised construction of a five-story reinforced-concrete building in Kabul, connecting structural requirements with site execution.
Developed and managed data-driven web applications, translating requirements into software workflows, APIs and interfaces.
Mentored junior developers and reviewed code and UI across 40+ projects.
Research and planning work spanning GIS, infrastructure, transportation, environmental planning and urban systems.
Technical capabilities
GCPIA · Veer Narmad South Gujarat University
Sardar Vallabhbhai National Institute of Technology (SVNIT)
Microverse · 1,300+ hours of intensive training
RESEARCH · COLLABORATION · OPPORTUNITIES