‘Delivering State-of-the-Art Imaging Data Science: Catalysis, Characterisation and Beyond’
Dr Aakash Varambhia, Data Science Lead at Johnson Matthey
Abstract:
Over the past few decades, the pursuit of cleaner energy, sustainable chemicals, and greener mobility solutions has reshaped industrial research and development. At Johnson Matthey (JM), this challenge has brought together a rich mix of materials scientists, chemists, engineers, computer scientists, and mathematicians, all working in concert. At the heart of this transformation is the ability to harness and interpret increasingly complex datasets, ranging from high-resolution microscopy images and detailed spectroscopic data, to correlative 3D tomographic reconstructions.
Central to JM’s approach is the integration of multi-lengthscale characterisation methods such as X-ray tomography (XRT), focused ion beam (FIB) tomography, and transmission electron microscopy (TEM) to capture hierarchical structures at varying length scales. This comprehensive pipeline reveals subtle correlations between structure and catalytic performance, from micron-level features uncovered by XRT, through meso- and nano-scale insights offered by FIB, down to atomic-level details exposed by TEM.
To handle the resulting volume and variety of data, JM has developed a flexible, scalable platform leveraging Python-based frameworks, parallel computing libraries, and cloud-based infrastructure. This ensures seamless workflows for data ingestion, preprocessing, analysis, and visualization, enabling swift collaboration, informed decision-making, and predictive modelling that iteratively refines both theory and experiment.
In this talk, Dr Varambhia will showcase JM’s data-driven research in catalysis science, highlighting how the interplay of advanced instrumentation, computational analytics and robust software ecosystems enables new levels of understanding.
About the Speaker:
Dr Aakash Varambhia leads the Advanced Characterisation Data Science team at Johnson Matthey’s Technology Centre. He and his colleagues Tom Ellaby, Zaeem Najeeb, and Dogan Ozkaya have pioneered the development of Python-based research platforms and analysis workflows. Their collective efforts ensure that scientists and engineers across JM have access to powerful, scalable tools for handling complex datasets. Through this approach, data science ceases to be a siloed function and instead becomes a core driver of innovation, complementing traditional experimental and theoretical techniques.
About Johnson Matthey:
With a distinguished history spanning more than two centuries, Johnson Matthey stands at the forefront of sustainable technologies, applying cutting-edge science to address pressing global challenges. The company’s solutions underpin a broad range of industries from clean energy and chemicals, to automotive applications enabling their clients, partners, and wider society to thrive. By integrating mathematical methodologies and advanced data interrogation with domain-specific knowledge, JM continually pushes the boundaries of what can be achieved, ensuring that research not only meets today’s demands, but also paves the way for a more sustainable tomorrow.
Schedule:
- 2.00pm – 3.00pm – Seminar + Q&A – G.07 (Heilbronn Room), Fry Building
- 3.00pm – 4.00pm – Refreshments and networking session – Common Room, Fry Building