Laboratory of Data Discovery for Health
A New Frontier of Global Health Protection with Deep Analytics
Chief Scientific Officer of D²4H
A New Frontier of Global Health Protection with Deep Analytics
Data analytics is set to play an important role in population health. There is a vacant niche for careful curation of data resources to develop novel, deep analytics that bridge private and public sector efforts while balancing scientific scrutiny. The Laboratory of Data Discovery for Health (D24H) has been launched to fill this gap with a mission to gather and curate massive, unique data resources and develop deep, frontier analytics to protect global public health while improving individual healthcare through precision medicine.
Apart from the collaborating institutions’ wide-ranging networks with other academic institutes nationally and internationally, D24H is keen to work with health authorities such as the World Health Organization and China Center for Disease Control and Prevention. D24H also aims to work with industrial partners like Tencent Healthcare and Microsoft Research on technology adoption and commercialisation efforts in global public health. The cross-disciplinary collaboration among academic, industry and civil organisations, and across geographical boundaries, is setting a new benchmark for world-wide impact.
D24H will focus on the following research activities:
- Mitigation of vaccine hesitancy across various types of social media and networks, particularly in American, European and Chinese communities
- Creation of next-generation virome-wide, immune-based technologies to detect infectious disease epidemics and understand their dynamics in the context of public health surveillance
- Global influenza monitoring and prediction, with anticipatory modelling and post-hoc assessment of mitigation measures
- Microbial metagenomics for pathogen discovery, phenomic correlation, drug and vaccine response prediction
- AI-driven disease treatment outcome prediction
- Pharmacovigilance at the population level
- Cloud-accelerated analytics for clinical-omics data
- Big-data-informed explainable predictive analytics for global health protection