Saakshi Singh
Brauer Monoid Factorisations using Machine Learning Techniques
This project aims to develop a Machine Learning (ML) model that is capable of factorising partition diagrams using a given presentation of the partition monoid. In doing so, it will explore the feasibility of using ML for applications in abstract algebra research and has the potential to significantly advance the tools available to algebraists.
Saakshi Singh
Western Sydney University
Saakshi Singh is a dedicated third-year undergraduate student at Western Sydney University, pursuing a degree in Mathematics and Data Science with a minor in AI. Driven by a passion for uncovering the profound intricacies of life through mathematics, she has gained effective problem-solving and critical thinking skills which heightens her passion for further research that remain unknown. Saakshi is deeply passionate about furthering her studies and envisions herself contributing to the field of research, leveraging her expertise to solve complex problems and unravel the mysteries of the universe. Eager to bridge the gap between theory and practical application, she aims to apply her knowledge in diverse professional settings, where she can manipulate mathematical concepts, analyse data, and derive meaningful insights.
Beyond her academic pursuits, Saakshi finds joy in exploring the world through travel, immersing herself in diverse cultures, and gaining unique perspectives that enrich her understanding of the world. She is an avid reader, finding solace in the pages of books that broaden her horizons, and a passionate music enthusiast.
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