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Dr Anjali Munde is a seasoned academic with a PhD in Mathematics and over 20 years of teaching and research experience in higher education. She holds Bachelor and master's degree in mathematics (Honours) from Hans Raj College, University of Delhi, where she was awarded the prestigious Gold Medal. In recognition of her commitment to high-quality teaching, curriculum innovation, and student-focused learning, she has been awarded Fellowship of the Higher Education Academy (FHEA) by Advance HE, UK. To augment her theoretical foundation with applied skills, she also completed a One-year Program in Data Science and Business Analytics, integrating advanced analytical methods into interdisciplinary research and practice.

Presently, she is working as a Senior Lecturer in Mathematics at ³Ô¹ÏºÚÁÏÍø, Malaysia. Prior to joining ³Ô¹ÏºÚÁÏÍø, she worked as an Assistant Professor of Business Analytics at University of Southampton, Malaysia. She has also worked at renowned institutions such as School of Inspired Leadership, Amity University, and Guru Gobind Singh Indraprastha University, Delhi, India.

She has conducted intensive interdisciplinary research that resulted in peer-reviewed publications indexed in ABDC, Scopus, and Web of Science. She has also presented technical papers at various national and international conferences, and chaired sessions, served on advisory and technical program committees in various IEEE and Soft Computing Research Society international conferences. She is a reviewer and editorial board member of several national and international journals. She has delivered several workshops and Faculty Development Programs on Data Analytics, Machine Learning, Python at prestigious institutions such as University of Delhi, Guru Gobind Singh Indraprastha University, ICMAI (The Institute of Cost Accountants of India), and many more.

She has extensive experience delivering modules including business mathematics, statistics, operations research, data mining, data analytics, machine learning, business forecasting, marketing analytics, data visualisation, predictive analytics, and many more. Her teaching embeds industry-relevant tools such as Python, R, Tableau, SPSS, and Excel to strengthen students computational, modelling, and visualisation skills. Her interdisciplinary research bridges data analytics, machine learning, predictive modelling, and text mining with applications in finance, sustainability, digital health, and consumer behaviour.