I am a multidisciplinary scientist, lecturer, and engineer with extensive experience across mechanical, automotive, chemical, and materials engineering. I hold a PhD in Mechanical Engineering from the University of Hull, where I investigated perforated acoustic liners for gas turbine combustors in partnership with Siemens. My earlier academic training includes an MSc in Automobile Engineering from City University London, a BSc in Mechanical Engineering from DUET, and a Diploma in Chemical Engineering.
My professional career spans academia and industry. I currently work as a Research Scientist at Loughborough University, leading the development of Model-Based Systems Engineering (MBSE) methods for Airbus’ Next-Generation Wing. My previous appointments include Postdoctoral Research Scientist in precision optics manufacturing at the University of Huddersfield, Lecturer at King’s College London in engineering disciplines, and Data Scientist in digital sensor technologies.
Across these roles, I have developed strong expertise in MBSE, MATLAB-based simulation, CAD design, robotic automation, acoustic analysis, and digital engineering. I have a sustained record of delivering high-impact research, supervising students, producing peer-reviewed publications, and collaborating with industrial partners on complex engineering challenges.
My doctoral research focused on understanding and improving acoustic damping mechanisms in full-scale combustor liners used in industrial gas turbines. I conducted a comprehensive programme of experimental measurements under high-temperature conditions and developed a semi-empirical hybrid model to predict liner impedance, transmission loss, and energy absorption. This work combined large-scale rig design, advanced data analysis, and mathematical modelling, and involved collaboration with Siemens Lincoln.
My ongoing research builds on this multidisciplinary foundation. At Loughborough, I design and implement MBSE system architectures for aerospace applications, integrating SysML, simulation frameworks, and digital engineering workflows to support Airbus’ next-generation wing development. I also contribute to simulation-based teaching innovation, creating AnyLogic and Insight Maker modules for system dynamics and discrete-event modelling.
My broader research interests include:
- Hybrid experimental–computational modelling
- Digital twins and simulation-led design
- Robotic polishing and precision manufacturing
- Acoustic systems and flow–structure interaction
- Sustainable engineering and system-level optimisation
My research spans acoustic engineering, digital engineering, and Model-Based Systems Engineering (MBSE), with a focus on developing rigorous experimental, computational, and system-level methods to solve complex engineering problems.
At the core of my work is the analysis and optimisation of acoustic energy absorption in gas turbine combustors. I developed full-scale experimental rigs, conducted high-temperature acoustic measurements, and created a semi-empirical hybrid model that predicts liner impedance, transmission loss, and energy dissipation. This model was validated against industrial datasets (including Siemens and DLR) and contributes to improved combustor stability, safety, and performance.
Personal interests include system modelling, robotics, simulation-based teaching, sustainable engineering, and supporting students from diverse backgrounds.
Publications: Elsevier
- Investigation of the Acoustics of Full-Scale Perforated Liners in Gas Turbine Combustors.
- Large Metal Mirrors for Atmospheric Telescopes.
- Validation and modification of a semi-empirical model for sound absorption by perforated liners in the absence of flow based on comparisons with data from full scale measurements.
- Bridging the Divide Between Iterative Optical Polishing and Automation.
- Benchmarking Machine Learning Models Against Full-Scale Acoustic Absorption Measurements in Gas Turbine Liners.