Jiadong Mao Lab

Statistics, Biology, and People

The Jiadong Mao Lab develops statistical methods, machine learning approaches, and computational tools for biomedical discovery. We are based at Melbourne Integrative Genomics (MIG), the University of Melbourne, and work closely with scientists and clinicians to analyse large, complex ’omics data.

Our current research program has two connected themes: modelling complex cell states, and uncovering the dynamics of cell state and disease progression. We work on single-cell and spatial omics data, multi-omics integration, and longitudinal data from clinical trials.

Research Themes

Complex Cell States

Statistical and computational methods for representing continuous, heterogeneous, and context-dependent cell states in single-cell and spatial omics studies.

Disease Dynamics

Models for understanding how cell states change across disease progression, treatment response, ageing, obesity, and other biological contexts.

Multi-omics Integration

Methods for connecting molecular, spatial, histological, and clinical data so that biomedical questions are addressed at the right biological scale.

Joining the Lab

We are interested in working with students, postdocs, clinicians, and scientists who enjoy interdisciplinary research. If you are curious about statistics, biology, machine learning, single-cell or spatial omics, please get in touch.

News

• Placeholder: add recent papers, grants, talks, student milestones, software releases, and recruitment notes.

Birth of a Naturalist

The lab website also keeps Jiadong’s essay series, Birth of a Naturalist, on the history of science, statistics, biology, and responsible scientific practice.