Software Engineering Graduate focused on AI Engineering - building AI-powered applications, machine learning workflows, cloud-backed platforms and full-stack software that can be inspected, improved and delivered professionally.
I like working across the full product path: understanding the problem, shaping the architecture, building the backend and interface, validating behaviour, documenting the system and preparing it for real users.
- AI product systems with practical workflows, role-based interfaces, evidence views and backend services.
- Machine learning projects with preprocessing, feature engineering, model comparison, evaluation and prediction outputs.
- Cloud and backend platforms using APIs, databases, deployment architecture, monitoring and documentation.
- Full-stack applications that connect usable interfaces with reliable data and business logic.
- Systems and software engineering projects involving concurrency, distributed components, Java/OOP design and clean project structure.
EduGuard - Flagship AI Academic Integrity Platform is the main project I want reviewers to inspect first. It combines React/TypeScript, FastAPI, PostgreSQL, Celery, RabbitMQ, Redis, plagiarism evidence review, AI-writing risk analysis, role-based dashboards, reporting, tests, screenshots, architecture notes, Postman collections, and performance smoke tests.
Why it leads the portfolio:
- It is the broadest end-to-end product in the portfolio, spanning frontend, backend, data, background jobs, and reviewer-facing workflows.
- It treats AI outputs as review evidence rather than automatic decisions, which shows product judgment as well as implementation.
- It includes proof assets inside the repository so a reviewer can inspect screenshots, setup, architecture, testing, API collections, and performance validation.
| Project | Focus | What it shows |
|---|---|---|
| EduGuard - Flagship AI Academic Integrity Platform | Flagship AI product / full-stack platform | End-to-end academic integrity system with plagiarism evidence review, AI-writing risk analysis, role-based dashboards, reports, feedback, analytics, tests, screenshots, and validation assets. |
| BLEVE Pressure Prediction ML | Machine learning | Feature engineering, preprocessing, CatBoost, XGBoost, SVR, neural networks, model comparison and prediction generation. |
| PitCrew Connect Cloud Deployment | AWS cloud platform | EC2, RDS MySQL, VPC, Apache/PHP, CloudWatch, EBS snapshots, load balancing, launch templates and Auto Scaling. |
| ASP.NET Core Banking Platform | Backend / full-stack | RESTful APIs, MVC web interface, SQLite database, account management, transactions, admin features and layered architecture. |
| P2P Job Swarm .NET | Distributed systems | Peer-to-peer job sharing, ASP.NET Core, WPF, SQLite, SHA-256 verification, Base64 encoding and dashboard monitoring. |
| C pthread Sorting Simulator | Systems programming | POSIX threads, mutexes, condition variables, shared state coordination and C concurrency fundamentals. |
Languages
Python | Java | C# | C | TypeScript | JavaScript | SQL
Backend, APIs and application frameworks
FastAPI | Flask | ASP.NET Core | REST APIs | MVC and layered architecture | Authentication workflows
Frontend, mobile and desktop UI
React | TypeScript | Tailwind CSS | Android | JavaFX | WPF
Data, AI and machine learning
Machine learning workflows | Feature engineering | Model evaluation | PostgreSQL | MySQL | SQLite | Jupyter Notebook
Cloud, DevOps and engineering tools
AWS EC2 | AWS RDS | VPC | CloudWatch | Docker | Git | GitHub Actions | Postman | Linux | Windows
AI / ML
EduGuard | BLEVE Pressure Prediction ML | AI-assisted academic integrity workflows
Cloud / backend / full-stack
PitCrew Connect | ASP.NET Core Banking Platform | Flask Web Security Lab
Distributed and systems engineering
P2P Job Swarm .NET | MKX Gaming Lobby WCF | C pthread Sorting Simulator | Air Traffic Simulator Java
Java / OOP / algorithms
JavaFX Maze Game Engine | Railway Network Simulator Java | City Grid Planner Java | Airline Route Planner DSA | Numerology Analyzer Java
Mobile and UX
Calorie Tracker Android | Connect Four Android | OnlyFit UX Case Study
- Understand before building - clarify the real requirement, constraints, users and failure paths.
- Design readable boundaries - keep APIs, data models, domain logic, integrations and UI responsibilities understandable.
- Build for evidence - use tests, validation, screenshots, reports, documentation and reproducible setup steps.
- Treat security as engineering - validate inputs, protect sensitive configuration and avoid exposing secrets.
- Finish professionally - a project is not done until another person can inspect, run, understand and maintain it.
Bachelor of Computing - Software Engineering Major
Curtin University, Colombo
- Completed degree requirements; graduation ceremony pending.
- Course Weighted Average: 78.71
- Dean's List: Year 2 Semester 2 and Year 3 Semester 2
- Strong results across cloud computing, machine learning, capstone project work, operating systems, distributed systems, mobile application development and software architecture.
Google AI Essentials
Coursera / Google Career Certificates - practical AI productivity, prompting, responsible AI use and modern AI workflows.
- Turning academic and personal projects into clean public engineering case studies.
- Strengthening AI engineering skills through Python, ML workflows, backend APIs and production-style project delivery.
- Building a portfolio that shows practical software range without losing focus on AI-powered systems.
Build useful systems. Validate the behaviour. Document the truth. Ship work that another engineer can trust.