Dr Varun Kumar Reja
- Marie Sklodowska-Curie Future Roads Fellow
- Assistant Professor, IIT Bombay, India
About
Dr. Varun Kumar Reja was a Marie Skłodowska-Curie Future Roads Fellow at the University of Cambridge. He obtained his joint Ph.D. from IIT Madras, India, and UTS, Australia, where he studied the use of computer vision for monitoring construction projects. His research area focuses on Automation in Construction, Digital Twins, and Construction Management. Prior to his current position, he was awarded the prestigious Prime Minister’s Research Fellowship (PMRF) at IIT Madras and received the UTS President's Scholarship (UTSP) and Collaborative International Research Scholarship (CIRS) at the University of Technology Sydney. He has rich on-field experience in project execution as a senior engineer, having worked in the industry with the Indian construction giant L&T. He is proficient in software applications like Revit, AutoCAD, Recap, and Rhino, and has a developing computer vision skillset. In the field, he specializes in Construction Engineering, Cost Management, and Project Execution. He holds a Master's degree (M.Tech.) focused on Construction Technology and Management from IIT Madras, which he obtained through the L&T - Build India Scholarship Program (BIS), and a Bachelor's degree (B.Tech.) in Civil Engineering from NIT Calicut.
Fellowship period: 15 June 2023 – 8 August 2025
Research
Strategic Themes
Infrastructure Management Supported by Digital Twins
Creating virtual replicas of physical infrastructure, such as buildings, roads, bridges, or utility systems, using advanced technologies like sensors, AI, and IoT.
Digital Twin Integration for Circular Construction
Investigate the use of digital twins in circular construction automation to improve material tracking, waste reduction, and optimize resource allocation throughout the construction lifecycle.
Computer Vision Based Infrastructure Assessment
Using advanced image processing / point cloud processing techniques to analyse and evaluate the condition and performance of various physical infrastructure, such as roads, bridges, buildings, and utility systems.
Research Project
Title: Mapping National Highway Requirements: Digital Twins for Road Operation and Maintenance
Theme: Digital Twins
Abstract:
Highway digital twins have emerged as powerful tools for asset maintenance, allowing for real-time monitoring and predictive analysis of infrastructure conditions. However, establishing the information requirements to implement these digital twins effectively remains a critical challenge. This research addresses this gap by identifying and delineating the essential information requirements to optimise highway digital twins for asset maintenance.
The methodology employed in this research involves a comprehensive approach that combines both quantitative and qualitative techniques. Initially, a thorough review of existing literature on highway digital twins and asset maintenance was conducted to identify standard practices and emerging trends. Subsequently, interviews and surveys were conducted with relevant stakeholders, including highway authorities, engineers, and technology experts, to gather insights into their information needs and preferences regarding digital twins. Data analysis techniques such as content analysis and thematic coding were then employed to distil critical findings and identify recurring themes.
Several essential information requirements for highway digital twins emerged through synthesising literature review findings and stakeholder input. Our model for establishing information requirements is based upon multiple road assets, each having their own maintenance stages influenced by several factors, and these factors are modelled based on time-stamped information requirements.
By delineating these requirements, highway authorities and infrastructure managers can better harness the potential of digital twins to improve maintenance practices, enhance operational efficiency, and ultimately prolong the lifespan of highway assets. Moreover, the emphasis on interoperability and data standardisation highlights the need for collaborative efforts and industry-wide standards to ensure the seamless integration of digital twin technologies into existing infrastructure management frameworks. Further research and development in this area are essential to address evolving challenges and capitalise on emerging opportunities in intelligent infrastructure management.
Alignment with SDG: This research contributes to SDG 9: Industry, Innovation, and Infrastructure and SDG 11: Sustainable Cities and Communities.
Project TRL: The current research is positioned at a TRL 4-5, focusing on validating key findings through controlled environments and stakeholder engagement.
Acknowledgement of Data and Collaborations: This research utilises the CAMHighways dataset, supplied for experimental purposes. Additionally, qualitative data has been gathered through interviews with experts from highway authorities and industry professionals.
Dr Varun Reja's key research interest lies in the areas related to Digital Construction Management. Specifically, he likes to explore the Digital Twin technology for infrastructure management, Use of metaverse in construction, and computer Vision applications.