ChM. Ts. Dr. Ong Song Quan
ChM. Ts. Dr. Ong Song Quan
Institut Biologi Tropika Dan Pemuliharaan · Institut Biologi Tropika Dan Pemuliharaan, UMS
songquan.ong@ums.edu.my
Summary

ChM Ts 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.

ChM. Ts. Dr. Ong Song Quan holds Sarjana Sains (Sains Data & Analitis) from Universiti Sains Malaysia , among other qualifications, and has established themselves as a respected expert in their field.

Education
Sarjana Sains (sains Data & Analitis)
Doktor Falsafah (ph.d)
Sarjana Sains (entomologi Gunaan)
Sarjana Muda Sains Gunaan (kepujian)
Stats
Publications:
68
Projects:
5
Grants:
RM 472,318.00
Scopus Metrics
Scopus Author ID:
56684128500
H-Index:
12
Documents:
51
Citations:
419
Research Interests
BIOLOGICAL SCIENCES - Entomology (Including Insect Taxonomy, Insect Pathology and Insect Toxicology)
Latest Grants
Prototype Development Of An Automated System For The Digitisation And Analysis Of Data From A Natural History Collection (nhc)
Vector Distribution And Molecular Characterization Of Japanese Encephalitis Virus (jev) In Sabah, Malaysia Borneo
Development Of An Intelligent System To Improve The Rearing Performance Of Black Soldier Fly Larvae (bsfl) For Animal Feed Production
Promotion Of Sustainable Green Control Technology For Vector And Pests In Sabah/borneo Malaysia
Latest Publications
Bornean Orangutan Nest Identification Using Computer Vision And Deep Learning Models To Improve Conservation Strategies
A Standardized Protocol For The Detection Of Arboviruses In Different Aedes Mosquito Species In North Borneo Sabah, Malaysia
Utilizing Machine Learning To Predict Hospital Admissions For Pediatric Covid-19 Patients (prepcovid-machine)
Comprehensive Analysis Of Beauty Community Discourse On Tiktok Through Gpt Embeddings And Bertopic Modeling
Mri-based Texture Analysis For Breast Cancer Subtype Classification In A Multi-ethnic Population
Previous Appointments
Administrative Positions