Song-Quan Ong is an entomologist and computational ecologist specialising in data- and technology-driven integrated pest management (IPM). He integrates artificial intelligence, data science, and field ecology to improve pest surveillance, decision-making, and sustainable control strategies. His work centres on leading interdisciplinary research projects, supervising postgraduate students, and translating advanced analytics into practical tools for pest management and biodiversity monitoring in agricultural and production landscapes.

With a strong foundation in entomology and computational ecology, Song-Quan’s expertise includes AI-based insect identification, computer vision for pest detection, ecological and spatial data analysis, and predictive analytics. His academic training spans entomology, data science, and computational ecology, including a postdoctoral fellowship at Aarhus University (Denmark), a PhD in Medical and Veterinary Entomology, and dual master’s degrees in Molecular Entomology and Data Science and Analytics. This unique combination enables him to bridge traditional pest ecology with modern tools such as deep learning, remote sensing, and digital surveillance systems to support precision agriculture and sustainable crop protection.

Throughout his career, he has collaborated with a wide range of academic, governmental, military, and industry partners, including the InsectAI group under European Cooperation in Science and Technology (COST), the Department of Veterinary Services Malaysia, the Armed Forces Research Institute of Medical Sciences (AFRIMS), the Naval Medical Research Unit Indo-Pacific (NAMRU2), different Natural History of Museum alongside Malaysian and international public health, agricultural, and conservation research teams. He has published extensively in high-impact journals such as Pest Management Science, Scientific Reports, and journals of the Entomological Society of America (ESA) etc, and is a frequent keynote and invited speaker on AI applications in entomology and pest management.

 

Outside his professional work, Song-Quan enjoys reading, reflective thinking, staying connected to nature, and exploring emerging technologies, which continually inform his systems-oriented approach to sustainable crop protection and ecological decision-making.