About

About

PhD Researcher · AI Engineer · Construction Tech Specialist

National Institute of Technology Karnataka, Surathkal

I am a researcher and AI engineer developing intelligent systems for the construction industry. My work bridges civil engineering and computer science, focusing on semantic frameworks, knowledge graphs, and natural language processing to transform how construction projects manage and utilize information.

Research Interests

Applied AI & Large Language Models
Retrieval-Augmented Generation (RAG)
Knowledge Graphs & Ontology Engineering
Building Information Modeling (BIM)
Natural Language Processing
Graph Neural Networks
Semantic Web Technologies
Digital Twins & Smart Cities

Research Overview

My doctoral research addresses the critical challenge of knowledge management in construction projects. The industry generates vast amounts of heterogeneous data—from BIM models and schedules to contracts and reports—yet this information remains largely disconnected and underutilized.

I develop semantic frameworks and AI systems that integrate construction project knowledge, making it queryable, analyzable, and actionable. My primary contribution is the IproK (Integrated Project Knowledge) ontology, a novel semantic model that unifies schedule, cost, and resource data into a coherent knowledge graph. This work has been published in the International Journal of Construction Management.

"The goal is not just to digitize construction data, but to make it intelligent—to create systems that understand project context, relationships, and temporal dependencies, enabling truly informed decision-making."

Beyond ontology development, I build practical applications: natural language interfaces for knowledge graph querying, multimodal RAG systems for document intelligence, and Graph Neural Network models for predictive project analytics.

Research Impact

125+ Total Citations
11 Publications
7 h-index
6+ Research Projects

Selected Publications

Kone, V. & Mahesh, G.

The IproK ontology: a unified approach to managing construction project information

International Journal of Construction Management, 2025, 1–30

Kone, V. & Mahesh, G.

An Ontology-Driven Bi-Directional Workflow for Integrating Project Management Data into The IFC Standard.

Journal of Information Technology in Construction, 2025

Accepted for publication

Kone, V. & Mahesh, G.

Ontology-Driven Project Management: A Framework for Structured Data and Automation

Proceedings of Digital Frontiers in Buildings and Infrastructure International Conference Series, 2025, 77-88

Kone, V., Mahesh, G., & Ingle, P.V.

Enhancing Knowledge Management in the Construction Industry: Exploring the Impact of Semantic Web Technologies

Advances in Construction Management. ICCRIP 2023. Lecture Notes in Civil Engineering, vol 601. Springer, Singapore

Munagala, D. P., & Kone, V.

Feasibility study and implementation of BIM in small scale projects

IOP Conference Series: Materials Science and Engineering, 2020, 912(6), 062049

Complete publication list available on Google Scholar

Key Research Projects

Doctoral Research

IproK: Integrated Project Knowledge Framework

GitHub →

Novel ontology-based framework for construction project knowledge management. Includes semantic data model (w3id.org/iprok/), web application for project planning and visualization, bi-directional BIM integration workflow, and GNN-based predictive analytics for risk assessment. Published in international journal.

Applied Research

ChatGraphDB: Natural Language Knowledge Graph Interface

GitHub →

LLM-powered conversational interface for querying construction project knowledge graphs. Achieves 82.5% accuracy in natural language to SPARQL translation. Transforms IFC models into queryable ontologies, enabling intuitive data access for non-technical stakeholders.

Applied Research

Multimodal Agentic RAG for Construction Contracts

GitHub →

Advanced retrieval-augmented generation system for analyzing complex construction documents. Handles multimodal content (text, tables, diagrams) through specialized pipeline combining Docling, ontology integration, vector databases, and agentic workflows for accurate context-aware information extraction.

Doctoral Research

Predictive Analytics for Project Control using Graph Neural Networks

GitHub →

Created a predictive model to forecast task-level delay and cost-overrun risks in construction projects. Engineered temporal, resource, and cost features from the IproK knowledge graph and used this data to train Graph Neural Network (GNN) models.

Education & Professional Experience

Ph.D. in Civil Engineering (Construction Informatics & AI)

National Institute of Technology Karnataka, Surathkal · 2020 – Present

CPI: 8.75 | Specialization: Knowledge Management, Applied AI, Semantic Web Technologies

Assistant Professor of Civil Engineering

KL University, Vijayawada · 2017 – 2020

Taught undergraduate courses, integrated computational tools into curriculum, mentored 15+ student research projects resulting in peer-reviewed publications.

M.Tech in Construction Technology Management

Visvesvaraya National Institute of Technology, Nagpur · 2015 – 2017

CPI: 7.19 | Focus: BIM Technology, Project Management Systems

B.Tech in Civil Engineering

J.B. Institute of Engineering and Technology, JNTUH · 2010 – 2014

Percentage: 74.10%

Scholarships

PhD Research Scholarship

Ministry of Education (MHRD), Government of India · 2020 – 2025

M.Tech Postgraduate Scholarship

Ministry of Education (MHRD), Government of India · 2015 – 2017

Professional Certifications

IBM RAG and Agentic AI: Build Next-Gen AI Systems Professional Certificate

Issued by: IBM (via Coursera) Verify →

Building AI Agents and Agentic Workflows Specialization Certificate

Issued by: IBM (via Coursera) Verify →

BIM Fundamentals for Engineers

Issued by: National Taiwan University (via Coursera) Verify →

Foundations of Project Management

Issued by: Google (via Coursera) Verify →

Technical Competencies

  • Python, JavaScript
  • TensorFlow, PyTorch, Scikit-learn
  • LangChain, LangGraph, RAG Systems
  • RDF, OWL, SPARQL, Turtle
  • Protégé, Owlready2, RDFlib
  • Apache Jena Fuseki, ChromaDB
  • Flask, FastAPI, Streamlit
  • Revit, NavisWorks, IFC Standards
  • Graph Neural Networks (PyG, DGL)
  • Natural Language Processing