About me

• Co-architected ePOP Pro, a 1M+ line compiled MATLAB desktop application deployed as a standalone executable to 10 enterprise clients; responsible for overall system design, module architecture, and code quality across a team of 6.
• Led development of core subsystems (Transmission Generator, Motor Generator) within a multi-domain physics engine covering mechanical, thermal, and electrical modelling — delivered to production and actively used by paying clients.
• Contributed to an in-house Simulink-to-MATLAB transpiler, enabling standalone deployment of simulation models without a Simulink runtime dependency.
• Formalised plugin architecture across a 1M+ line organically grown codebase: introduced clear module boundaries, dependency contracts, and a plugin registry — significantly reducing coupling and onboarding time for new engineers.
• Introduced CI/CD from scratch: GitLab CI / GitHub Actions pipelines, automated unit testing frameworks, and structured code review processes across the team.
• Pioneered adoption of AI-assisted development across the engineering team: rolled out Claude Code to engineers' local environments, integrated automated AI code review into the CI/CD pipeline, and built custom agentic workflows — delivering an estimated 5× increase in individual engineer output.
• Led backend API development for ePOP Concept, a 500k line web-based simulation platform (Angular / TypeScript); designed and built a REST API integrating AWS DynamoDB with the front-end simulation environment, enabling real-time architecture composition from a live component database.
• Designed combinatorial search algorithms evaluating up to 500,000 architecture permutations against multi-criteria customer requirements.

MATLAB · Python · Simulink · C# · TypeScript · Angular · REST APIs · AWS DynamoDB · GitHub Actions · JIRA · Confluence · Claude Code

• Defined and owned the software engineering strategy for a team of 4–7 engineers: introduced Git branching workflows, coding standards, code review culture, CI/CD pipelines, and a structured mentoring programme — taking the team from ad hoc scripting to production-quality engineering practice.
• Rearchitected a large inherited MATLAB/Python analysis codebase for vehicle dynamics tooling, rebuilding for testability, modularity, and long-term maintainability.
• Delivered LHAS (Limited Handling and Stability), a production analysis tool used daily by 20 in-house vehicle dynamics engineers to process and analyse data from proving ground tests — translating raw test data into actionable engineering insight across the handling and stability discipline.
• Contributed to ATOM (Application Toolbox for Objective Metrics), a vehicle build tracking platform with a SQL database backend and MATLAB UI frontend, used by 500 engineers across JLR — serving as version control for vehicle configurations across the full development programme.
• Partnered with domain engineers to translate complex analytical requirements into well-specified, maintainable software; drove adoption of Agile/Scrum across the team.

MATLAB · Python · Git · CI/CD · Agile/Scrum · JIRA · Confluence

• Tech Lead for a cross-functional team of 11 engineers spanning chassis, body, and powertrain disciplines — coordinating delivery across workstreams while maintaining hands-on technical contribution.
• Built and led delivery of: Simulink-based analysis tools, desktop MATLAB applications, interactive web dashboards, and automated reporting pipelines — all shipped to internal stakeholders.
• Designed and managed data pipelines from a 350-vehicle engineering fleet into GCP / BigQuery; reduced manual data processing across the organisation.

MATLAB · Simulink · Python · SQL · GCP / BigQuery · Microservices · Web Dashboards

• Developed production MATLAB CAE applications within an Agile team; applied ML and numerical optimisation to automate vehicle tuning workflows previously done manually.
• Designed and delivered FRM (Fast Ride Model), a reduced-order vertical dynamics simulation tool combining a Simulink 18-DOF vehicle model backend with a MATLAB UI frontend, adopted by 20 engineers across the vehicle dynamics simulation department. FRM reduced full simulation sweep time from 90 minutes to 90 seconds (a 60× speed-up) while maintaining accuracy within 90% of the original.
• Designed fleet data pipeline architecture that became the foundation for the Data Science team.
• Objective and subjective vehicle testing on public roads and proving ground; findings presented to senior engineering leadership.

MATLAB · Python · Simulink · SIMPACK · JIRA · Confluence

• Investigated image sensor degradation under real-world noise conditions for ADAS applications; trained DNN classifiers using MATLAB Automated Driving Toolbox.

MATLAB · Python · MATLAB Automated Driving Toolbox

• Built signal processing pipelines and trained ANNs (MATLAB and Python) to predict human ride comfort from biometric and vibration data — published in peer-reviewed journals and presented internationally.
• Hands-on vehicle test programme design and execution in a professional automotive test environment.

MATLAB · Python · TensorFlow · Keras