Call for papers
Important dates
15 Nov 2026
Abstract submission deadline
30 Nov 2026
Abstract acceptance
15 Dec 2026
Full paper submission
30 Dec 2026
Final acceptance
15 Jan 2027
Early registration closes
31 Jan 2027
Final registration closes
25–26 Feb 2027
Conference
Research areas
Original, unpublished papers are invited in the following areas, but are not limited to them.
01AI, machine learning and digital twins
- Predictive maintenance and fault diagnosis
- AI-based design and topology optimisation
- Digital twins and condition monitoring
02Advanced design and manufacturing
- Machine design and mechatronics
- Additive manufacturing (3D printing)
- Advanced welding and joining technologies
- CAD / CAM / CAE and reverse engineering
- Traditional and non-traditional machining
03Robotics and smart automation
- Intelligent robotics and autonomous systems
- Industry 4.0 and Industrial IoT
- Digital manufacturing and smart systems
04Energy, thermal and fluids
- Computational fluid dynamics (CFD)
- Electric vehicles and automotive engineering
- Hydrogen energy and clean technologies
- Energy storage and sustainable engineering
05Materials and precision engineering
- Advanced engineering materials
- Surface engineering and coatings
- Metrology and quality engineering
06Other engineering disciplines
- A limited number of AI/ML manuscripts from disciplines other than mechanical engineering will be considered
How to submit
- 1.
Submit an abstract of your original, unpublished work by 15 November 2026.
- 2.
Authors of accepted abstracts submit the full paper by 15 December 2026.
- 3.
Full papers are peer reviewed; final acceptance is announced by 30 December 2026.
- 4.
Accepted papers are presented in person. Foreign delegates may present online.
Download the abstract template from this page. The full paper template and the submission portal will be published here. For questions, write to icaimle2027@nitw.ac.in.
Acknowledgement. The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.