Research Areas

My research spans a broad but connected set of themes across chemical engineering, chemistry, and materials science.

1. AI and Data-Driven Chemistry

I work on the development and application of AI and data-driven techniques for chemistry-related problems, including molecular and materials discovery, pattern extraction from chemical datasets, and chemically informed modelling frameworks. This includes interest in practical chemistry applications such as dye development and broader molecular design problems.

2. Porous Materials and Metal–Organic Frameworks

A central part of my research concerns porous materials, especially metal–organic frameworks (MOFs), with emphasis on their physical, physicochemical, and structure–property behaviour.

3. Adsorption, Gas Storage, and Separation

I work on adsorption science and separation problems, including both molecular-level understanding and process-oriented perspectives relevant to gas capture, gas storage, and selective separations.

4. Process Modelling for Separation Applications

I am interested in process modelling approaches for adsorption and separation systems, especially where rigorous engineering insight can be combined with data-driven methods to improve understanding, screening, and design.

5. Catalysis

My research interests also extend to catalytic materials and catalytic phenomena, especially where materials chemistry, structure, and reactivity can be connected in an interpretable manner.

6. Structure–Property Relationships

A major theme across my work is understanding how composition, topology, defects, morphology, and local chemical environment affect observable performance and behaviour in chemical and materials systems.

7. Interpretable Scientific Machine Learning

I am particularly interested in interpretable and trustworthy machine learning approaches for scientific problems, where the goal is not only prediction but also insight, chemical relevance, and robust generalisation.

Current Direction

My current direction is centred on developing scientifically rigorous and practically meaningful research programmes that combine chemical engineering, materials science, and AI-driven analysis. I am especially interested in questions where computational methods, experimental relevance, and chemical understanding can be brought together in a way that is useful for both academic research and real-world technological applications.