Hi, I'm Imran
Software Engineer & Embedded Systems Developer skilled in Simulink, MATLAB, automotive validation, and automation using Jenkins and Gradle
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Education
BS Computer Engineering – AUBH (2020 – 2024)
- Dean’s List (2021–2023), Active Citizen Award
- Founder & President – Sustainability Club
- Relevant Courses: Digital Circuits, Operating Systems, Embedded Systems, Software Design and Engineering, Windows Programming, Machine Learning and Data Analytics, and Microprocessors.
A-Levels – British School of Bahrain (2018 – 2020)
- Subjects: Math, Physics, Chemistry, Further Maths (A/A/A/A)
- President – Sustainability Club, Head Ambassador
Experience
Graduate Intern – McLaren Automotive Ltd Jul 2024 – Jun 2025
- Built scalable backend infrastructure to support the migration of legacy data using Express.js, TypeScript, SQL Server, and integrated with a Next.js frontend for real-time visualization.
- Developed MATLAB and Python solutions to streamline testing workflows. Automated Simulink model validation, reducing manual effort and review time. Created Python scripts to address Git/SVN sync issues across 20+ repositories and manage test case breakdowns for requirements.
- Administered user access and role-based permissions for Jenkins, RhodeCode, and Artifactory, and resolved Jenkins-to-Azure SQL data transfer issues, restoring Power BI reporting and enabling clearer visibility into key test reports.
D-Lab Intern – AUBH (Jan 2024 – May 2024)
- Developed and deployed a full-stack e-commerce platform using Next.js, Supabase, and Three.js to streamline access to 3D printing lab services.
- Enabled real-time 3D model previews for users, improving submission accuracy and enhancing the overall user experience.
Teaching Assistant – AUBH (Sep 2023 – May 2024)
- Designed and taught lab sessions for Introduction to Machine Learning and Data Analytics (CMPE 390) in Fall 2023 and Principles of Electrical Engineering (ELEC 204) in Spring 2024.
Programming Instructor – Algorithmics (Dec 2023 – Apr 2024)
- Taught programming fundamentals to students aged 10–16 using Python, C++ (via Unity), and visual programming tools like Scratch.
Projects
- All
- Front End
- Back End
- Embedded/Controls
- Machine Learning

McLaren Backend REST API
Built scalable backend infrastructure to support the migration of legacy data using Express.js, TypeScript, SQL Server, and integrated with a Next.js frontend for real-time visualization.

Skills
Languages
- Python
- Matlab/Simulink
- Typescript/Javascript
- C++/C
- Java
- Groovy
- SQL/KQL
- Bash
Frameworks & Libraries
- Express
- Next.js
- React
- Flask
- Pandas
DevOps & Tooling
- Git
- SVN
- Jenkins
- Azure
- Shell Scripting
- Postman
- Swagger
- Jira
- Artifactory
- DOORS
- JAMA
Embedded & Hardware
- Arduino
- Raspberry Pi
- HIL Testing (Vector, dSPACE SCALEXIO)
- ECU Flashing & Validation
- Simulink Model Verification
- Test Rig Integration
Publication
Research and academic contributions
Smart Wireless Sensor for Machine’s Health Condition Monitoring
Published: Jun 8, 2024 – American University of Bahrain (AUBH)
This study explores an innovative approach to Micro-Electro-Mechanical Systems (MEMS) sensor networks for machine monitoring using modern wireless technology. It focuses on developing a vibration-based wireless MEMS sensor network for industrial settings, enabling remote, real-time data collection to identify early faults. The initial phase emphasizes designing highly sensitive, reliable sensors capable of operating in various environments and selecting materials and technologies for accuracy, robustness, and miniaturization.
A key aspect is incorporating a low-power wireless module to extend sensor life and reduce maintenance costs. The design phase also covers developing a database for structured sensor data and a website for end-user access. The implementation phase involves testing and developing five prototypes, addressing challenges in sensor system components to ensure robust data transmission and maximum sensitivity. The study assesses sensor performance in measuring vibration, pressure, and temperature, and examines data processing and analysis capabilities for converting sensor signals into analyzable data.
View Publication