Haiting Chai

Dr. Haiting Chai is a computational biologist and data scientist with a background spanning genomics, bioinformatics, machine learning, and virology.

His work focuses on translating complex biological and clinical questions into structured, data-driven insights that support research and real-world application. He is particularly interested in bridging data and decision-making in areas such as viral genomics and host–pathogen interactions, where analyses must be both scientifically rigorous and practically meaningful.

Dr. Chai works across interdisciplinary environments, integrating clinical and biological data from diverse sources to enable robust analysis and interpretation. His work involves shaping datasets, defining research questions, and applying analytical approaches to better understand disease processes in clinically relevant contexts. He places strong emphasis on recognising the limitations of real-world data and ensuring findings are interpreted with appropriate context.

He also contributes to the development of scalable and reproducible analytical frameworks, supporting collaboration and consistency across projects. Working closely with multidisciplinary teams, he translates complex results into clear, actionable insights for both technical and non-technical audiences.

Dr. Chai collaborates with clinicians, geneticists, and computational scientists on multidisciplinary studies across international cohorts. His research spans multiple viral diseases, including hepatitis C virus (HCV), hepatitis B virus (HBV), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), dengue, and human immunodeficiency virus (HIV), with a focus on generating biologically and clinically meaningful insights.

His broader interests lie in computational genomics and the application of data science to healthcare and life sciences, particularly where analytical approaches can connect research with real-world outcomes.