Emerging Computational Models for Scientific Discovery

Marjana Prifti Skënduli

Emerging Computational Models for Scientific Discovery

Author(s)	Dr. Marjana Prifti Skënduli
Country	Albania
Abstract	The rapid growth of computational capabilities has fundamentally transformed the process of scientific discovery by enabling researchers to analyse complex systems, process massive datasets, and develop predictive models beyond the limitations of traditional analytical approaches. Emerging computational models combine artificial intelligence, machine learning, high-performance computing, simulation techniques, and data-driven approaches to accelerate knowledge discovery across scientific disciplines. This research examines Emerging Computational Models for Scientific Discovery by analysing how advanced computational frameworks contribute to hypothesis generation, scientific modelling, predictive analysis, and interdisciplinary research innovation. The study adopts a conceptual research approach based on theoretical perspectives related to computational science, artificial intelligence, scientific modelling, data analytics, and digital research transformation. The analysis highlights that computational models enable researchers to explore complex phenomena through simulation, pattern recognition, automated reasoning, and intelligent prediction. Artificial intelligence-based models, deep learning systems, foundation models, and hybrid computational frameworks are creating new possibilities for scientific investigation in fields including physics, biology, chemistry, environmental science, and engineering. The study identifies major challenges associated with emerging computational models, including computational resource requirements, model interpretability limitations, data quality issues, reproducibility concerns, ethical considerations, and the need for interdisciplinary expertise. Effective utilization requires transparent methodologies, responsible AI practices, and collaboration between computational scientists and domain experts. The research concludes that emerging computational models represent a significant transformation in scientific discovery by extending human analytical capabilities and enabling new forms of knowledge creation. Future scientific ecosystems will increasingly depend on intelligent computational frameworks that integrate automation, human expertise, and advanced modelling approaches.
Keywords	Computational Models, Scientific Discovery, Artificial Intelligence, Machine Learning, Scientific Computing, Data-Driven Research, Knowledge Discovery
Field	Engineering
Published In	Volume 8, Issue 5, September-October 2026
Published On	2026-09-30

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American International Journal of Research and Innovation

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Emerging Computational Models for Scientific Discovery

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