Dr. Norli Anida is an applied statistician specializing in statistical modeling, discriminant analysis, predictive analytics, and data-driven decision-making. Her work focuses on translating quantitative methods into practical solutions across interdisciplinary domains, including medical statistics, environmental analytics, educational innovation, and talent development. Her research in craniomaxillofacial statistics has contributed to predictive modelling and applied medical analytics, while her recent work extends to water quality assessment, industry-focused quantitative modelling, and AI-enhanced educational systems. She currently leads several funded research and innovation projects, including the development of valuation and risk management models for oil portfolios under a university–industry talent building collaboration with PETCO, as well as exploratory data analysis and principal component analysis of Sungai Klang, Skudai and Perai Basin water quality with PSTW. Dr. Norli is also the Principal Investigator & Founder for The DegreeMate App, an AI-driven initiative that supports personalized academic pathways aligned with industry demand, and serves as a co-researcher and trainer for The Entrepreneurial University Programme (The Catalyst Project), an international initiative on innovation and entrepreneurship in higher education. In addition, she is involved as a co-researcher in the Ministry of Higher Education (MOHE), Malaysia project, Hala Tuju Penyelidikan KPT dalam RMKe-13. Since 2021, Dr. Norli has served as the Managing Editor of the Journal of Statistical Modeling and Analytics (JOSMA), where she has played an active role in strengthening the journal’s publication quality and visibility. The journal is currently under evaluation for indexing in Scopus and Web of Science. In teaching and learning innovation, Dr. Norli received the E-Learning Innovative Award and was selected as a finalist for the Anugerah Khas YB Menteri Pendidikan Tinggi: Rekabentuk Kurikulum dan Penyampaian Inovatif (AKRI) for her project on integrating traditional mathematics tutorials with AI tools. She is passionate about leveraging statistics, analytics, and technology to strengthen evidence-based practices, foster innovation in education, and nurture future STEM talents.

Dr. Asmiza Sani is a senior lecturer and presently the Head of the Software Engineering Department at the Faculty of Computer Science and Information Technology, Universiti Malaya. She is deeply engaged in academic leadership, teaching, and curriculum development for undergraduate and postgraduate programs in software engineering and computer science. Her research interests include model-driven engineering, application framework development, software engineering education, algorithm design and analysis, and real-time systems. Her scholarly work aims to enhance software engineering practices and learning through structured engineering methodologies, alternative assessment approaches, and technology-enhanced environments within higher education and applied technology contexts. Additionally, she investigates the integration of artificial intelligence, the Internet of Things (IoT), machine learning, deep learning, and digital twin technologies to develop intelligent and adaptive systems. Beyond her research pursuits, Dr. Asmiza actively contributes to curriculum review processes, program accreditation, and continuous quality improvement initiatives aligned with national and international standards in higher education. Her academic vision is to advance software engineering education and to develop sustainable, intelligent, and digital systems methods and techniques that effectively bridge academia and industry.

Muhammad Ashraf Bin Khalid is a Senior Lecturer at the Department of Decision Science, Faculty of Business and Economics, Universiti Malaya. He obtained a Bachelor of Science in Computational Mathematics from Universiti Teknologi MARA, and later earned his Master of Applied Statistics and PhD from Universiti Malaya. His academic and research work centres on applied statistics, with particular emphasis on data computing, analytics, and quantitative research applications. He also has research interests in men's health issues, especially disparities in health outcomes between men and women at both national and global levels. He is also involved in consultancy and collaborative research-related work with national and international organisations, including the National Population and Family Development Board (LPPKN), an agency under Malaysia's Ministry of Women, Family and Community Development, and the United Nations Development Programme (UNDP). Through these engagements, he has contributed his expertise in statistical analysis, data-driven research, and evidence generation to support policy, programme development, and applied social research.