Mrs. Nur Insani
Details
College: School of Science
Department: School of Science
Campus: City Campus Australia
nur.insani@rmit.edu.au
ORCID: 0000-0003-1494-8874
About
I am a lecturer & researcher in mathematics, statistics and data science, with extensive experience in university teaching and research. I hold a PhD from RMIT University and a Master's degree from Monash University. My academic interests span statistical modelling, data analytics, machine learning, optimisation and computational methods. I have taught a wide range of mathematics, statistics and data science courses and have supervised undergraduate and postgraduate research projects. I am particularly interested in applying quantitative and computational methods to real-world problems across diverse application areas.
Teaching interests
I have extensive experience teaching mathematics, statistics, data science and related computational subjects at undergraduate and postgraduate levels. My teaching areas include introductory and applied statistics, statistical computing, data visualisation and communication, machine learning, and data analytics. My teaching emphasises the connection between statistical and mathematical concepts and their practical applications. I incorporate real-world datasets and computational tools such as R, Python, SAS, Minitab, SPSS and other data analysis platforms to help students develop practical problem-solving, analytical and communication skills.
Research interests
My research interests include statistical computing, data science, machine learning, optimisation, and data visualisation. I am particularly interested in the development and application of computational and machine learning methods for analysing complex and high-dimensional data. My research also includes classification and predictive modelling, neural networks, ensemble learning, feature selection, explainable machine learning, clustering, time-series analysis, and optimisation. I am interested in interdisciplinary applications of these methods to real-world problems in health, education, finance, transportation, and decision-making.
