Advanced AI/ML Solutions for High-Energy and Low-Energy Physics, Chemistry, and Applications in Mathematics and Biology
Scientific research across multiple domains, including high-energy and low-energy physics, chemistry, mathematics, and biology, requires innovative computational tools to solve complex problems, model systems, and interpret vast datasets. Artificial Intelligence (AI) and Machine Learning (ML) offer powerful solutions to these challenges, enabling automation, optimization, and the extraction of meaningful insights from complex datasets.
SRIBS seeks the development of AI/ML-based solutions that can:
Physics (High and Low Energy): Automate data analysis for high-energy and low-energy particle simulations, spectroscopic experiments, and accelerator data.
Chemistry: Predict and simulate chemical reactions, molecular dynamics, and reaction pathways using AI-driven models.
Mathematics: Solve advanced mathematical problems, including optimization, differential equations, and system modeling, using machine learning algorithms to aid in discovery and verification.
Biology: Model biological processes such as protein structure prediction, gene expression analysis, and metabolic pathway simulation through AI-driven predictive models and data analysis tools.
