Song-Quan Ong 王松灌
Entomologist, Chemist and Data Scientist
Ts ChM Dr Ong Song-Quan is a Senior Lecturer at the Institute of Tropical Biology and Conservation (ITBC), Universiti Malaysia Sabah. He is one of the pioneers in Malaysia using next generation technologies in precision biodiversity and digital health. In recent years, his research has focused on the digitisation of insect specimens, including a 3D model that can be used in a computer-generated environment such as virtual reality and the metaverse. His expertise extends to cross-disciplinary research that impacts the community, including the application of artificial intelligence and data analytics in biodiversity conservation and public health. He holds a PhD in Medical and Veterinary Entomology, a Masters in Molecular Entomology and a second Masters in Data Science and Analytics. As a data scientist, licenced chemist and medical entomologist, he is able to leverage the overlap between these disciplines and make a meaningful contribution to biodiversity conservation and public health. Dr Ong's research has been published in numerous publications including prestigious journals such as 'Parasites & Vectors', Nature Research's 'Scientific Report'/ 'Scientific Data', 'Pest Science Management', etc.
I was born in Johor, Skudai, where I also spent my childhood. I did my secondary schooling in Seremban, Negeri Sembilan, and completed my undergraduate and postgraduate degrees in Penang. I started my career as an entomologist and chemist specialising in insect toxicology and semiochemical extraction. In recent years, I have focused more on the power of machine learning and data analysis to address the problem of public health and biodiversity conservation respectively. For example, one of the studies I have applied machine learning to is the classification of two closely related mosquito species - Aedes aegypti and Aedes albopictus. Both mosquito species are known to transmit dengue fever, but Ae. aegypti can also transmit yellow fever and Zika virus. Knowledge of the prevalence of these species in the population helps public health professionals plan strategies to control and, if possible, eradicate these mosquitoes in densely populated areas with human habitation.
A novel approach to estimate the abundance of house fly larvae