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. Erialdi Syahrial is a senior lecturer at the Faculty of Business and Economics, Universiti Malaya (UM), Malaysia. He served as a Visiting Researcher at Goddard School of Business and Economics, Weber State University in Utah, United States. As a Visiting Researcher, he presented his research at the Annual Conference of the Production and Operations Management Society (POMS) in Florida, United States. Before transitioning to academia, Dr.Erialdi worked at PROTON, Malaysia’s first national car manufacturing company, where he held roles as Section Head, Lead Engineer, and Project Leader in the Research and Development (R&D) Department. Additionally, he has worked on after-sales service projects in the United Kingdom, Italy, Korea, and Germany. Dr.Erialdi’s work involved collaborating with CEOs, managing directors, customers, suppliers, and consultants from several countries. He is a member of the Board of Engineers Malaysia (BEM) and is recognized by the Malaysia Board of Technologists (MBOT) as a Professional Technologist (Ts.) until 2023. After his tenure at PROTON, Dr. Erialdi pursued a Doctorate of Philosophy (Ph.D.) in Japan, earning his Doctoral degree in Engineering from Keio University in Yokohama. His teaching and research interests primarily focus on Supply Chain Management, Logistics Management, Operations Management, Project Management and Quality Management. In 2022, Dr. Erialdi served as a session chair at the Asia Pacific Conference on Industrial Engineering and Operations Management. In 2024, he was appointed as a panel speaker and session chair at the International Conference on Industrial Engineering and Operations Management (IEOM) in Dubai, UAE, as well as panel chair and session chair at the Asia Pacific Conference on IEOM in Tokyo, Japan. In 2024, he also chaired sessions at the International Conference on ICT Application Research and the Malaysia-Japan Visionaries Conference in Tokyo, Japan. In early 2025, he contributed to the 15th Annual IEOM Singapore as a technical committee member, session chair, and paper reviewer. Additionally, he met with the IEOM CEO and COO during IEOM Singapore to establish the IEOM Student Chapter at UM. Dr. Erialdi is currently an active project member at Universiti Malaya, working on a project funded by the Malaysian government. In Universiti Malaya, he has established initial connections with governments, universities, institutions, and agencies both nationally and internationally for potential future collaborations.

Associate Professor Dr. Anis Salwa Mohd Khairuddin is currently affiliated at the Department of Electrical Engineering, Faculty of Engineering, Universiti Malaya. She is also a Chartered Engineer registered under the Engineering Council, U.K. and a member of IEEE Computational Intelligence Society (CIS). In addition, she serves as Malaysia Focal point for Sub-Committee on Microelectronics and Information Technology (SCMIT) in ASEAN COSTI (from year 2020 until current). The Committee on Science, Technology & Innovation (COSTI) is responsible for operationalizing and translating the APASTI strategic thrusts into specific actions.  As for administrative responsibilities, she was the Final year Project (FYP) Coordinator from 2015/2016 until 2019/2020. Consecutively, she was appointed as the Outcome-Based Education (OBE) coordinator since 2020/2021 until 2023/2024. Currently, she is the Head of Department for the Department of Electrical Engineering, Faculty of Engineering, Universiti Malaya. In addition, she serves as the Head of Centre of Intelligent Systems for Emerging Technology (CISET), Faculty of Engineering, UM. Her research expertise lies in pattern recognition area, focusing on the application of artificial intelligence by developing computationally intelligent algorithms for spatial and temporal signal processing.  She works on the application of machine learning methods to solve various pattern recognition problems in precision agriculture, smart manufacturing, and energy management. Researcher ORCID : https://orcid.org/0000-0002-9873-4779 ResearcherID : https://www.webofscience.com/wos/author/record/B-5340-2010 Researcher profile : https://umexpert.um.edu.my/anissalwa Google scholar : https://scholar.google.com/citations?user=zIYCmHAAAAAJ