Former position

Enrichment Student

Cohort year


Partner Institution


Ranjith K. Soman is a doctoral student at the Centre for Systems Engineering and Innovation in Imperial College London. He spent a semester (October 2018-Mqarch 2019) at the Turing as an enrichment student to support his PhD work. His research is funded through a  Skempton scholarship and a research grant from Bentley systems UK. His doctoral research focuses on implementing data-driven methods to improve construction planning in modular offsite construction. Before moving to Imperial College London, he obtained MSc (by research) in building technology and construction management from Indian Institute of Technology Madras in India. His master’s thesis focused on developing an automated construction progress monitoring system for monitoring metro rail construction.

Research interests

In the construction sector, new forms of project delivery are emerging that enable more rapid and agile forms of organising. These use the digital infrastructure of computers, mobile devices, sensors, network connections and application platforms,  which, in the construction phase, have the potential to permeate and transform activities and relationship across the construction site and office. However, during the construction stage, unstructured data is distributed among different teams and domains. This limits the application of data science on this data to gain insights on the project information and limits possibilities of automation. Ranjith’s research focuses on addressing this problem by developing a method to codify the information in the construction stage using linked data in modular offsite construction. He uses linked data to model process information including but not limited to resource information and activity information as data graphs and uses Shape constraint language to model constraint information as shapes graph. Also, the data graphs are linked to the product information in Buiding  Information Models. He plans to demonstrate the potential of the codification by automating look ahead planning in modular offsite construction.