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@article{189032,
author = {Ayushman Shukla and Arav Singh and Aradhya Jain and Ansh Mishra and Anshika Singh and Harshit K Singh},
title = {Artificial Intelligence and Machine Learning Research: Applications in Mechanical Engineering and Beyond},
journal = {International Journal of Innovative Research in Technology},
year = {2025},
volume = {12},
number = {7},
pages = {4369-4378},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=189032},
abstract = {Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative technologies reshaping virtually every engineering discipline. This paper provides a comprehensive analysis of accessible and practical AI/ML research projects specifically designed for high school and undergraduate students, with emphasis on applications within mechanical systems, automation, and mechanical design optimization. Through systematic examination of twenty distinct research initiatives spanning Natural Language Processing, Computer Vision, Recommender Systems, and Time Series Analysis, this paper identifies entry-level opportunities for novice researchers to develop meaningful contributions while building foundational AI/ML capabilities. Special attention is directed toward projects demonstrating direct applicability to mechanical engineering challenges including predictive maintenance, manufacturing optimization, robotic vision systems, and mechanical design automation. The paper concludes with evidence-based recommendations for project selection, implementation strategies, dataset management, and ethical considerations in AI research. All projects are executable using free cloud resources and open-source frameworks, ensuring accessibility for students in resource constrained environments.},
keywords = {Artificial Intelligence, Computer Vision, Deep Learning, Machine Learning, Mechanical Engineering, Neural Networks, Natural Language Processing, Predictive Maintenance, Research Methodology, Transfer Learning},
month = {December},
}
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