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Jharkhand News: IIT ISM team wins IndiaAI Hackathon on mineral targeting

Jharkhand News: IIT ISM team wins IndiaAI Hackathon on mineral targeting

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Jharkhand News: IIT ISM team wins IndiaAI Hackathon on mineral targeting

Jharkhand Story by Jharkhand Story
19 November 2025
in Blog
Jharkhand News: IIT ISM team wins IndiaAI Hackathon on mineral targeting
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SUBHASH MISHRA

 

Dhanbad, Nov 19: An IIT ISM Dhanbad team from the Department of Applied Geophysics has won the IndiaAI Hackathon on mineral targeting, marking a major achievement for the institute and strengthening India’s push toward AI-driven mineral exploration.

IIT ISM’s AI Model Wins National Recognition

The winning team, led by Prof. Partha Pratim Mandal, assistant professor in Applied Geophysics, developed an advanced AI-driven mineral targeting system called CricSM AI.
The award was presented in New Delhi by Prof. Ajay Kumar Sood, Principal Scientific Advisor to the Government of India; S. Krishnan, Secretary; Abhishek Singh, Additional Secretary; and senior officials from the Ministry of Electronics & Information Technology (MeitY).

Strong Collaboration Behind the Winning Project

Other members of the IIT ISM team included Dr. Pradeep Kumar Shukla, Litan Dutta, Dinesh Munda, Tanmay Singh, and Sai Satyam Jena. They worked under Prof. Mandal’s leadership to create a highly advanced system for strategic mineral mapping.

ALSO READ: Dry, cold conditions to prevail in Jharkhand

An IIT ISM official said the national-level competition, organised by MeitY, aimed to harness the potential of artificial intelligence in mineral exploration across India.

‘CricSM AI’ Stands Out for Nationwide Mineral Mapping

According to the institute, CricSM AI was recognised for its ability to map critical and strategic minerals across key regions such as Jharkhand, southern Rajasthan, Karnataka, and Andhra Pradesh.
This capability places the project among India’s most advanced attempts at AI mineral detection.

Advanced Models Power High-Accuracy Mineral Prediction

The project combined large language models (LLMs), the Naini model, ensemble machine learning approaches, and convolutional neural networks (CNNs).
These technologies allowed the system to predict and map deposits of gold, diamond, graphite, rare earth elements, copper, iron, and manganese, complete with uncertainty quantification.

This integration of advanced AI tools positions CricSM AI as a significant breakthrough in AI-supported geoscience and machine learning-based mineral discovery.

Major Leap for India’s AI in Natural Resource Discovery

The IIT ISM team produced a highly precise mineral prospectivity map, followed by depth analysis for concealed and deep-seated deposits.
This achievement reinforces India’s growing emphasis on cutting-edge AI innovation in the field of geoscience, strategic mineral mapping, and natural resource discovery.

 

 

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