BioAI Research
Principal Investigator : Girinath G. Pillai
BioAI Research Group at the CVJ Centre for Synthetic Biology and Biomanufacturing focuses on the integration of artificial intelligence (AI), systems biology, and bioprocess engineering to enable predictive and scalable biological design. The central theme is to move biological research from largely empirical approaches toward data-guided and model-informed engineering of biological systems.
BioAI develops computational and experimental frameworks that connect molecular-level properties with cellular behaviour and process performance.
This includes the use of machine learning, mechanistic modelling, and multi-omics data integration to better understand genotype–phenotype relationships and to improve predictability in biological systems.
A major focus is the implementation of Design Build Test Learn (DBTL) cycles, where experimental data are continuously incorporated into models to refine predictions and guide subsequent design for translational research products.
These iterative workflows support:
Overall, the BioAI theme aims to establish predictive and adaptive bioengineering workflows that can accelerate research and development in synthetic biology, industrial biotechnology, and sustainable biomanufacturing. The long-term goal is to contribute to the development of reliable, scalable, and data-driven biological production platforms that support the growing bioeconomy.