Sydney Precision Data Science Centre

Extracting insight from the data deluge

We are a world-leading precision data discovery centre that facilitates data decision making in the areas of health and wellbeing, food sciences, conservation, and biomedicine.

The Sydney Precision Data Science Centre aims to realise the University's collective research potential, make ground-breaking foundational discoveries using data-intensive science, and answer the complex  challenges in biology, medicine and global health. 

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Our aims

The purpose of the Sydney Precision Data Science Centre is to engage in high quality and transformational multidisciplinary research and to provide a research hub to all interdisciplinary researchers in data-intensive science.

We generate innovative, fit-for-purpose applied analytical methodologies that are critical to knowledge discovery through the deep integration of various quantitative disciplines and research paradigms.

Sydney Precision Data Science Centre members

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Our research

Kidney allocation data science

This project brings together biostatistics and bioinformatics disciplines to deliver a series of tools to improve kidney disease management and access and transplantation outcomes.

Cardiovascular data science

The project combines expertise in bioinformatics, machine learning and statistics to integrate multi-omics data to create novel biomarkers and risk scores for coronary artery disease that is flexible, interpretable and scalable. This will close the gap between data generation and data interpretation and the gap between biomarker discovery and clinical translation.

Data discovery for health (D24H): infectious disease

This project brings together expertise in bioinformatics, imaging and machine learning to develop a suite of readily deployable software solutions that accelerate the processing of various biomedical data by harnessing the parallel and distributed capacity offered by modern cloud computing platforms.

Cancer data science

This is a collection of cancer projects that requires expertise in statistics, biostatistics, imaging and machine learning to develop a suite of tools including genomics and imaging omics, that will solve major challenges in multi-morality risk prediction tools. The projects have a primary focus on melanoma and head and neck cancer.

Single-cell data science

The project embraces disruptive biotechnologies such as the recent single-cell innovation that generates thousands or even millions of cells in a single experiment and poses unique data science problems in scale and complexity. As such, it generates new computational and algorithmic challenges related to data storage, processing (including normalisation), modelling, analysis, and interpretations.

Population food quality and supplies for health

This project combines statistics, biostatistics, demographic modelling and age-period-cohort models to address data challenges associated with food quality and supplies. This includes projects that involve understanding globally competitive Australian meat value chains as well as the effects of contemporary and historical food supplies on health.

Nutriomics for healthy aging

This project brings together biostatistics, precision bioinformatics and computational statistics to address pressing issues in nutritional science. This includes evaluating the effects of dietary macronutrient composition on disease outcome to facilitate healthy aging and incorporating large-scale ‘omics’ datasets to address the multi-dimensional complexity of nutritional problem.

Stay in touch

Director
Professor Jean Yang

Email
data-science.admin@sydney.edu.au