Dr. Hazwan Ariff Hakimi is an architect and academic specialising in architectural history, theory, and philosophy, with a sustained research focus on architectural and cultural heritage and Islamic art and architecture. He holds a PhD in Architecture from Universiti Kebangsaan Malaysia (Graduate on Time with Excellent Thesis) and a Master of Arts in Architectural History (Distinction) from The Bartlett, University College London. His academic training reflects a strong commitment to critical historiography, theoretical inquiry, and interdisciplinary scholarship. Dr. Hazwan’s research investigates architecture as a spiritual, cultural, and ethical practice, with particular attention to Islamic and non-Western contexts. Through peer-reviewed journal articles, scholarly book chapters, and conference publications, his work advances contemporary debates on meaning, memory, and continuity in the built environment. In teaching, Dr. Hazwan plays an active role in shaping architectural education at both undergraduate and postgraduate levels. He encourages students to integrate theoretical reflection, historical understanding, and cultural sensitivity into architectural thinking and design practice, foregrounding intellectual coherence across theory, research, and studio work, and fostering critical inquiry and scholarly rigour. Alongside his academic career, Dr. Hazwan has professional experience as a design architect, with contributions to projects including Rica Residence in Kuala Lumpur and City International Hospital in Ho Chi Minh City. He is a registered member of the Board of Architects Malaysia (LAM), the Malaysian Institute of Architects (PAM), the Royal Institute of British Architects (RIBA), and the Historians of Islamic Art Association (HIAA). He also serves in editorial, reviewing, and academic service roles, reflecting his commitment to advancing architectural scholarship and supporting the next generation of researchers. Dr. Hazwan actively welcomes research collaborations and postgraduate supervision in architectural history, theory, and philosophy, architectural and cultural heritage, and Islamic art and architecture. His ongoing work seeks to bridge philosophy and practice, tradition and modernity, and theory and place, contributing to an architectural discourse that is historically grounded, culturally attuned, and intellectually rigorous.

Dr. Adediran Anthonia Oluwatosin is a Senior Lecturer in the Department of Real Estate, Faculty of Built Environment, Universiti Malaya, with over 13 years of academic experience. She holds a PhD in Real Estate from Universiti Teknologi Malaysia, focusing on housing finance; a Master’s in Real Estate Development and Investment from the University of Greenwich, UK; and an HND in Estate Management from Yaba College of Technology, Nigeria. She also completed specialized training in Data Science in Real Estate at the MIT School of Architecture and Planning, USA. Before joining UM, she served as an Adjunct Assistant Professor at the Federal University of Uberlândia, Brazil and a lecturer at the Federal Polytechnic, Ado-Ekiti. Her research interests include housing finance, housing affordability, green finance, PropTech, data analytics, energy efficiency, and sustainable real estate development. She has published extensively on machine learning applications in renewable energy, climate change, and housing, with several papers indexed in Scopus and Web of Science. Dr. Adediran applies advanced econometric modeling, statistical analysis, and big data analytics in her work. She supervises postgraduate students, teaches real estate finance and analytics-related courses, and contributes to program development and faculty committees.

Ts. Dr. Siow-Wee CHANG is an Associate Professor in the Bioinformatics Programme at the Institute of Biological Sciences, Faculty of Science, Universiti Malaya, Malaysia. She earned her Ph.D. in Artificial Intelligence (AI) from Universiti Malaya. To date, she has published over 40 papers in reputable journals and conference proceedings at both local and international levels. Her research spans artificial intelligence (AI), data science, bioinformatics, and medical informatics, with a strong interdisciplinary approach that bridges life sciences, medicine, and computer science. She applies AI to advance biomedical research, focusing on disease diagnosis & prognosis, biomarker discovery, and drug discovery & repurposing. Her studies integrate AI-driven methods, multi-omics data integration, gene expression analysis, and spatial transcriptomics to identify potential disease biomarkers and therapeutic candidates. She also applies computational drug screening, molecular docking, and AI-driven predictive modeling to accelerate pharmaceutical research.  Beyond biomedical research, Siow-Wee Chang applies machine learning and deep learning in agricultural studies, particularly in plant species identification and crop disease detection. Her works focus on uncovering patterns in crop data and analyzing their relationships, contributing to advancements in precision agriculture, plant health monitoring, and data-driven farming solutions.