AI-Driven Research Methodologies: Revolutionizing Data-Driven Discoveries in Engineering and Physical Sciences

Abstract

This chapter examines how artificial intelligence (AI) is changing how engineering and physical science researchers do their work. It demonstrates how artificial intelligence (AI)-driven technologies—like machine learning deep learning and predictive analytics—are transforming conventional approaches by making it possible to process and analyse enormous datasets at previously unheard-of speeds and precision. In fields where sophisticated simulations and data patterns have produced ground-breaking discoveries such as materials science renewable energy aerospace engineering and manufacturing the chapter explores the integration of AI in these fields. It also discusses how AI can stimulate interdisciplinary collaboration increase predictive power and improve research efficiency. The chapter also covers obstacles such as the requirement for transparent algorithms ethical issues and data biases. The usefulness of these developments is demonstrated through case studies of effective AI applications in scientific research.

Keywords: Artificial Intelligence (AI), Machine Learning (ML), Deep Learning, Predictive Analytics