Computer vision · Digital twins · Construction intelligence

Computer vision.
Digital construction.

I am Dr. Shanmugaraj Senthilnathan. I develop computer vision and sensing methods that connect physical construction processes with digital models, turning observations into decisions for quality, productivity, and reliability.

Portrait of Dr. Shanmugaraj Senthilnathan

Postdoctoral Researcher, Technical University of Munich
Ph.D., Building Technology and Construction Management, IIT Madras

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Explore my research ↓ Academic CV ↗
Computer vision detection of pipeline construction activity in a field image Individual concrete layers extracted from images for dimensional analysis
Computer vision / From pixels to measurements Visual intelligence for construction processes Detect activities, extract geometry, and track changes in quality and progress.
01 / 04
Technical University of MunichPostdoctoral research
IIT MadrasPh.D. & M.Tech.
L&T Construction3 years of EPC experience

01 / RESEARCH

Making construction
processes observable.

Computer vision is the connecting method across my work. I combine imaging, multimodal sensing, and digital models to understand how construction processes evolve, then use that evidence to support monitoring and control.

Postdoctoral research · TUM · Ongoing Industrial robot and deposition equipment in the laboratory

Multimodal sensing & adaptive operations

Combining computer vision and laser profiles to assess geometry, deformation, and repeatability in robotic fabrication. Within TRR 277, this includes sensing for closed-loop control of shotcrete deposition.

Broader direction: fuse optical, mechanical, and ultrasonic evidence with physical constraints to estimate material state and inform parameter adaptation.

Postdoctoral research · TUM · Ongoing Concrete production digital twin framework, with material characterisation and feedback along the supply chain

Digital twins for concrete production

Connecting material characterisation and process information from batching through transport, pumping, and placement. My work explores how optical measurements and rheological evidence can represent evolving material state and support feedback across the production process.

Research directions: camera and laser sensing, correlation with yield stress and viscosity, and integration with concrete production and mobile robotic workflows.

Master’s research · IIT Madras Pipeline construction activity identified by computer vision in a site photograph

Computer vision for project progress

Turning GPS-tagged smartphone images into location-specific progress information for pipeline-laying projects. Convolutional neural networks identify field activities and connect observations to the digital project model in AutoCAD.

Construction management purpose: improve the timeliness and consistency of progress information across dispersed work fronts. M.Tech. thesis recognised by L&T Construction in 2019.

Postdoctoral research · TUM · Ongoing Bridge structural monitoring sensor installation

Digital twins for bridge structural monitoring

Linking physical infrastructure to numerical models through a multi-property sensor network. The research connects local durability and stiffness indicators with measured structural response to inform condition assessment and action strategies.

Focus: sensor-to-model integration, strain measurements, structural analysis, and the relationship between local deterioration and global behaviour.

DOCTORAL RESEARCH / IIT MADRAS

Process and quality monitoring in 3D concrete printing.

My Ph.D. used concrete 3D printing as a setting for a broader process-monitoring problem: how can computer vision detect changing process conditions and guide action before quality or reliability deteriorates?

From visual measurements to process decisions

  1. Observe the processExtract individual layers and quantify geometry, deformation, surface texture, and voids from image sequences.
  2. Assess quality and reliabilityTrack temporal changes to identify buildability risk and quantify extrudability evolution.
  3. Support corrective actionUse interpretable visual signals to inform printing-speed and auger-speed adjustments.

Experimental programme: 107 large-scale prints and 3,810 layers. The wider contribution is a sensing-to-decision framework for reliable construction processes.

Concrete printing experiment showing the element before collapse
Why process monitoring matters Experimental sequence showing progressive layer deposition followed by buildability failure.
Open original GIF ↗
Computer vision analysis linking image measurements and concrete printing process behaviour
Visual measurements connect observed deformation with process behaviour.
Layer surface comparison without and with active auger control
Surface-quality assessment provides evidence for material-delivery control.

A management question
at the centre.

How can construction systems sense, predict, and act before quality, time, or resource failures occur? My research connects digital observations with decisions about process waste, productivity, and the reliability of construction operations.

02 / PUBLICATIONS

Selected publications.

Publications on computer vision for process monitoring, digital fabrication, and construction quality assessment. Published titles link to DOI records; accepted work is labelled separately.

162 Google Scholar citations ↗ As of
2026Accepted

Buildability Supervisory Decision Support in Concrete 3D Printing Using Image Data

S. Senthilnathan and B. Raphael

Materials and Structures · Accepted for publication (2026). DOI pending.

03 / INDUSTRY EXPERIENCE

Construction management,
from the field.

Before my doctoral research, I worked in the Water & Effluent Treatment Independent Company (IC) of Larsen & Toubro Construction, India, in EPC project planning and coordination. Responsibility for schedules, resources, and project interfaces gave me a practical foundation for research in construction monitoring and decision support.

3 years EPC planning & coordination
INR 1,200 crore Project planning responsibility
7 EPC projects Project coordination experience
Large concrete structure under construction, with formwork, reinforcement and scaffolding
Civil construction works in water and effluent treatment infrastructure.
Construction-site view of a reinforced concrete structure and surrounding excavation
Site execution context: coordinating civil works, resources, and project interfaces.

May 2019 – May 2020 · L&T Construction · Water & Effluent Treatment IC, India

Assistant Planning Manager

Single point of responsibility for planning, monitoring, and resource management of an INR 1,200-crore EPC project.

  • Planning and project control. Maintained detailed construction schedules and monitored project progress.
  • Client coordination. Coordinated directly with the client on planning and monitoring responsibilities.
  • Execution interfaces. Worked across client, supply chain, contract, and labour-management interfaces.

June 2015 – July 2017 · L&T Construction · Water & Effluent Treatment IC, India

Senior Engineer – Project Coordination

Project coordinator for seven EPC projects, connecting procurement, design, planning, monitoring, and project management.

  • Cross-functional coordination. Worked across design and procurement interfaces to support project execution.
  • Stakeholder and contract interfaces. Experience in stakeholder management, design coordination, supply chain management, and contract management.
  • Planning and monitoring. Coordinated project information and activities across multiple EPC projects.
  • Mentoring. Trained junior engineers and personally mentored two graduate trainees who progressed to senior engineer roles.
EPC system illustration showing an intake well, pump house, elevated tank and delivery chamber
Water infrastructure system linking intake, pumping, storage, and delivery.

Connecting industry, research & teaching

Better information for construction decisions.

Planning and coordination depend on knowing what is happening on site, how resources are being used, and where interfaces need attention. These responsibilities inform my research on computer vision, digital twins, and process monitoring.

They also provide a practical context for teaching construction planning, project management, contracts, and digital methods.

04 / TEACHING

Management fundamentals.
Digital depth.

My teaching connects construction management fundamentals with computer vision, data analysis, and digital models. Students move from a practical construction question to a working computational method and an evidence-based decision.

Teaching experience

  • Instructor & guest lecturerClasses for bachelor’s and master’s students in introductory Python, machine learning, and deep learning model development.
  • Teaching assistant, IIT MadrasMachine Learning in Construction
    Repair and Rehabilitation of Concrete Structures
    Construction Contracts
  • Invited talk“Buildability Failure Prediction Using Computer Vision,” Loughborough University, UK.

05 / ACADEMIC BACKGROUND & CO-CURRICULAR ACTIVITIES

Academic background.
Co-curricular activities.

My academic training in construction management supports my work in computer vision and digital construction. Alongside research and teaching, I contribute through peer review, conference coordination, and outreach.

Research & education

Current

Postdoctoral Researcher

Technical University of Munich

Chair of Materials and Methods in Digital Construction. Advisor: Prof. Dirk Lowke.

2020–2025

Ph.D., Civil Engineering

IIT Madras · Building Technology and Construction Management

Computer Vision-Based Quality Monitoring and Control of Concrete 3D Printed Elements. Advisor: Prof. Benny Raphael.

2017–2019

M.Tech., Civil Engineering

IIT Madras · Building Technology and Construction Management

Computer Vision-Based Progress Monitoring of Linear Pipeline Laying Projects. Advisor: Prof. Benny Raphael.

2011–2015

B.E., Civil Engineering

PSG College of Technology, Coimbatore

Co-curricular activities

Peer review

Journal reviewer

  • Automation in Construction
  • Journal of Building Engineering
  • Engineering Structures
2023

Lead student coordinator, ISARC 2023

40th International Symposium on Automation and Robotics in Construction, IIT Madras. Also coordinated the Point Cloud Workshop.

Outreach

Conference and workshop volunteering

Volunteer contributions to multiple conferences and workshops, including ISARC 2022 and the Concrete 3D Printing Workshop.

2023

Head Liaison Officer, G20

Led 30 liaison officers for the Education Working Group meeting in Chennai, coordinating with the Indian and Saudi Arabian education ministries.

06 / PROPOSED RESEARCH PROGRAMME

Digital process systems
for construction.

My five-year research vision connects process intelligence with construction management, with the goals of reducing rework, improving productivity, and supporting sustainable operations.

Thrust A

Sensing & prediction

Computer vision and multimodal sensing to identify activities, measure change, and predict process or asset deterioration.

Thrust B

Planning & digital twins

Connect production processes, project progress, and infrastructure condition with digital models for planning and operational decisions.

Thrust C

Robotics & feedback control

Translate sensed process conditions into adaptive robotic operations and coordinated workflows involving people and machines.

06 / CONTACT

Let’s connect.

I welcome research collaborations in computer vision, digital twins, construction process monitoring, and intelligent infrastructure systems.

Dr. Shanmugaraj Senthilnathan
Technical University of Munich
Munich, Germany

shanmugarajcode94@gmail.com ↗

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