MLGH-SG

We are a group of researchers and students at the National University of Singapore who are part of the broader Machine Learning & Global Health Network. Within the university we are spread across Saw Swee Hock School of Public Health, NUS Institute of Data Science and Department of Statistics and Data Science. Our research focuses on applying and developing generative AI, and statistical machine learning techniques for the broader and messier world of science and public policy, especially global health. We develop flexible and scalable models for understanding various spatiotemporal data.

We are committed to open science and reproducible research. We are a diverse group of researchers with backgrounds in computer science, statistics, mathematics, engineering, epidemiology, and public health. We value diversity and inclusion and are committed to creating a supportive and inclusive environment for all members of our group. We are always looking for new collaborations and opportunities to work with other researchers and organizations. If you are interested in working with us, please feel free to reach out to us.

Areas of research include:

• Applied research in:
  • Epidemiology and public health
  • Non-communicable disease burden
  • Semi-mechanistic modelling of infectious disease dynamics
  • Online information diffusion
  • Crime modelling
  • Healthcare
• Methodological research in:
  • Disease transmission modelling
  • Phylogenetics
  • Bayesian statistics and Bayesian nonparametrics
  • Computational statistics and machine learning
  • Spatiotemporal statistics
  • Generative deep learning
  • Survey design
• Theoretical research in:
  • Machine learning and deep learning
  • Graphs and networks
  • Kernel methods
  • Stochastic point processes