Parag is a quantitative researcher and data specialist with training in mathematics, molecular biology, and engineering.

He completed a BSc (1997) with a double major in Mathematics and Molecular Biology at University of Newcastle, and a BE (Hons) in Bioprocess Engineering at UNSW (2000), with a strong interest in the applied mathematics of bioreactor and process design. He is currently undertaking part-time MSc research at UNSW.

His research interest is in integrating multi-omics measurements with bioreactor process data to identify drivers of yield and variability in yeast bioprocesses, and to build predictive and interpretable models that support strain and process optimisation. His current work involves sourcing multi-omics datasets, applying rigorous quality control and cleaning, and preparing integrated, normalised features for downstream analysis. He plans to extend this with modern machine-learning methods (e.g., graph neural networks and variational autoencoders).

He also brings over 20 years of industry experience building reproducible analytical workflows and large-scale data pipelines across complex, heterogeneous datasets. His industry experience helps him manage complex datasets, build quick prototypes, and scale them into reliable, reproducible analyses.