๐Ÿ“ข PhD Advertisement Open | Last Date: 10th May 2026  ยท  Apply Now โ†’
Digital Twin and Industrial AI Lab โ€” DIAL

Digital Twin and Industrial
Artificial Intelligence Lab

Led by Dr. Pradeep Kundu
Assistant Professor ยท Department of Mechanical Engineering ยท Indian Institute of Technology Indore

We Develop Condition Monitoring, Prognostics & Health Management, Predictive Maintenance, Quality Control, and Process Monitoring Solutions to Ensure Zero-Down Time and Zero-Defect Manufacturing

Applications
Defence Aerospace Space Wind Turbines Smart Manufacturing Process Industries
Explore Research Join the Lab
50+
Publications
1
Patent
15+
Industry / Academic
Collaborations and Engagements
20+
Keynote & Invited
Talks
10+
Conference
Committees
5+
Editorial
Positions
Dr. Pradeep Kundu
Assistant Professor ยท IIT Indore
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About

Dr. Pradeep Kundu

Current Position
Jan. 2026 โ€“
Present
Assistant Professor
Department of Mechanical Engineering, Indian Institute of Technology (IIT) Indore, India
Past Experiences
Feb. 2023 โ€“
Dec. 2025
Assistant Professor
Department of Mechanical Engineering & Institute for Artificial Intelligence, KU Leuven, Belgium
Feb. 2022 โ€“
Jan. 2023
Postdoctoral Fellow
Center for Intelligent Maintenance Systems, University of Cincinnati, USA
Dec. 2020 โ€“
Jan. 2022
Research Associate
Centre for Precision Manufacturing, University of Strathclyde, UK

Dr. Pradeep Kundu is an Assistant Professor in the Department of Mechanical Engineering at IIT Indore. His research has significantly advanced the scientific foundations of condition monitoring, predictive maintenance, process monitoring, and quality control through Digital Twin technologies and Physics Integrated Artificial Intelligence (hybrid modelling).

His work addresses three major challenges that limit the industrial deployment of asset health management solutions: overcoming data scarcity for training reliable machine learning models, enhancing the interpretability and robustness of AI-driven prediction frameworks, and developing standardised domain-specific signal denoising strategies.

His research spans diverse engineering systems including rotating machinery (bearings and gears), precision motion and feed-drive systems, robotic manipulators, machine tools, micro-manufacturing, semiconductor processes, hydrogen fuel cells, and composite structures.

Research Vision

Research Focus & Core Challenges

Overview

DIAL develops Condition Monitoring and Prognostics & Health Management solutions, as well as Quality Control and Process Monitoring solutions across diverse engineering systems (listed below). We leverage Artificial Intelligence, Hybrid Modeling, Digital Twin, Signal Processing, and Reliability Engineering technologies to develop these solutions. How these technologies address core challenges is described on the right.

Engineering Systems

Bearings & Gears Feed-Drive Systems Robotic Manipulators Machine Tools Micro-Manufacturing Semiconductor Processes Hydrogen Fuel Cells Composite Structures

Core Challenges Addressed

  • i
    Overcoming data scarcity for training reliable ML models in industrial settings using Digital Twin technology
  • ii
    Enhancing interpretability & robustness of AI-driven prediction frameworks by developing Reliability-Based Models and Physics-Informed Machine Learning Models (Hybrid Modeling)
  • iii
    Developing standardised signal denoising strategies for industrial domains based on Domain-Based Feature Engineering and Physics-Informed Signal Denoising

Selected Key Publications

A complete list of publications related to my research can be found at my Google Scholar page. The following selected works provide an overview of the group's research activities across our core themes:

01
02
Domain Driven Signal Denoising New Feature Development Prognostics & Health Management Condition Monitoring Gear
03
04
Physics Modelling Hybrid Modelling Prognostics & Health Management Condition Monitoring Gear
05
Domain Driven Signal Denoising New Feature Development Prognostics & Health Management Condition Monitoring Motion Control Systems
06
07
Reliability-Based Modelling Prognostics & Health Management Condition Monitoring Process Monitoring Quality Control
08
Digital Twin Prognostics & Health Management Condition Monitoring
09
Machine Learning Process Monitoring Quality Control
10
11
View Full Publication List on Google Scholar
Community & Leadership

Roles & Impact

5+
Editorial Leadership
Most recent:
2025 โ€“ Present
Associate Editor
Artificial Intelligence Review, Springer IF 13.9
2025 โ€“ Present
Associate Editor
Measurement, Elsevier IF 5.6
2025 โ€“ Present
Associate Editor
Digital Twins and Applications, Wiley
10+
Conference Leadership
Most recent:
2026
Honorary General Chair
2025 Prognostics and System Health Management Conference, Marseille, France
2026
Co-Chair
Smart & Circular Manufacturing. Sustainable Production Technologies Track, ASME IMECE India 2026 Conference
2025
General Chair
2025 Prognostics and System Health Management Conference, Bruges, Belgium
2025
Award and Data Challenge Chair
PHM Asia Pacific 2025, Singapore
Teaching

Courses Taught

2026 ยท IIT Indore, India
CourseRoleLevelProgramme
Quality Management Main Lecturer Undergraduate BTech in Mechanical Engineering
2023 โ€“ 2025 ยท KU Leuven, Belgium
CourseRoleLevelProgramme
Digital Twin Deployment in Manufacturing Industry Main Lecturer Advanced Master Advanced Master of Science Programme in Smart Operations & Maintenance in Industry
Operations Management Strategies Main Lecturer Advanced Master Advanced Master of Science and Post Graduate Certificate Programme in Smart Operations & Maintenance in Industry
Decision Support for Maintenance Logistics Co-Lecturer Advanced Master Advanced Master of Science Programme in Smart Operations & Maintenance in Industry
Digital Twin Co-Lecturer Advanced Master Advanced Master of Science and Post Graduate Certificate Programme in Smart Operations & Maintenance in Industry
Reliability and AI Co-Lecturer Master Master in Industrial Sciences: Electromechanics
Industry & Academic Partnerships

Past & Current Collaborations and Engagements

Dr. Kundu has developed various aspects of the Digital Twin and Industrial AI pipeline in collaboration/engagements with 15+ industries and academic partnerships. Key of them are listed here:

KU LEUVEN
Belgium
Ghent University
POLITECNICO
DI MILANO
1863 ยท Italy
Universidad Carlos III de Madrid
HITACHI
High-Tech
NIST
National Institute of
Standards & Technology
HIWIN
POCLAIN
Hydraulics
MITSUBISHI
ELECTRIC
CNH
INDUSTRIAL
ฮด
Delta
ENGINEERING
CTRL
engineering
SIEMENS
mainnovation
GE
Join the Lab

Prospective Students & Collaborators

DIAL welcomes interest from motivated interns, PhD students, postdoctoral researchers, and industry collaborators. We offer a rigorous, collaborative environment to work on high-impact problems at the intersection of Digital Twin, Machine Learning, Physics-Integrated AI, and Reliability Engineering for solving various problems related to Condition Monitoring, Prognostics & Health Management, Predictive Maintenance, Quality Control, and Process Monitoring in various applications such as:

Defence Aerospace Space Wind Turbines Smart Manufacturing Process Industries
Get in Touch
Announcements

Lab Notices

๐Ÿค Industry Collaboration DIAL is actively seeking industry partners for collaborative R&D projects. Reach out to discuss partnership opportunities.
๐Ÿ“ข PhD Advertisement Open | Last Date: 10th May 2026 PhD positions open at DIAL, IIT Indore. Click here for more information โ†’
๐Ÿ”ฌ PostDoc Applications DIAL welcomes applicants to apply for the PostDoc under the ANRF PDF Scheme. Prospective PostDoc candidates should contact Dr. Kundu before submitting the application as host at DIAL, IIT Indore.
๐ŸŽ“ Intern Applications Prospective interns need to apply through the IIT Indore website. Applications are closed for Summer 2026. Click here for more information โ†’
Contact

Get in Touch

๐Ÿ“
Department AddressDepartment of Mechanical Engineering, IIT Indore, Simrol, Indore, Madhya Pradesh โ€” 453 552, India
๐Ÿข
Office AddressRoom Number: 211-D, Computer and Information Technology Center, IIT Indore, Simrol, Indore, Madhya Pradesh โ€” 453 552, India
โœ‰๏ธ
Emailpkundu@iiti.ac.in
๐Ÿ“ž
Phone+91 7316603333 (Ext. 5311)
๐Ÿ”ฌ
LabDigital Twin and Industrial AI Lab (DIAL), IIT Indore
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