About
Product owner and applied data scientist with 7+ years of experience in delivering enterprise ML/GenAI solutions. Track record of partnering with academia to translate research into deployable products. Shaped product strategy, roadmap and adoption framework to embed cutting edge LLM tools into enterprise BAU workflows. Entrepreneurial founder with a solutions-driven mindset and proficiency in taking ideas from 0-to-1 through rigorous experimentation and stakeholder alignment creating measurable impact.
My research focuses on applied machine learning that is reliable at scale. On the scientific side, I develop ML pipelines for high-throughput microscopy to quantify drug-induced cellular changes and accelerate cancer research. On the enterprise side, I design and deploy GenAI systems on cloud platforms with an emphasis on safety, robustness, and cost-aware MLOps. A core thread is AI cybersecurity—mapping threat vectors across data, model, and deployment layers—and translating them into governance patterns, evaluation harnesses, and guardrails. Broadly, I’m interested in human-centred, interpretable AI that delivers measurable value in healthcare, finance, and the public sector.
Publications
Rittick Barua, Kevin McCay, Mohammed Al-Khalidi, Yonghong Peng, Jamie Crossman-Smith
Cyber security risks to artificial intelligence (Whitepaper)
Department of Science, Innovation and Technology - 2024
Adam Colbourne, Thomas Blythe, Rittick Barua, Sean Lovett, Jonathan Mitchell, Andrew Sederman, Lynn F Gladden
Validation of a low field Rheo-NMR instrument and application to shear-induced migration of suspended non-colloidal particles in Couette flow
Journal of Magnetic Resonance - 2018
Barua, R., Lee, K., Mills, N., Ouki, S., Thorpe, R.
The effects of steam explosion and hydrolysing time on the digestibility of sewage sludge in anaerobic digestion
AcquEnviro - 2014