| π Specialization | π Current GPA | π Academic Status |
|---|---|---|
| Data Science | 4.00 / 4.00 | Undergraduate @ SLIIT |
I am a third-year B.Sc. (Hons) Information Technology undergraduate student specializing in Data Science at the Sri Lanka Institute of Information Technology (SLIIT). I design intelligent solutions using multi-agent AI systems, machine learning architectures, and modern web tech.
| Category | Technologies |
|---|---|
| Languages | Python Java JavaScript SQL C |
| Artificial Intelligence | CrewAI Google Gemini API RAG FAISS ChromaDB |
| Machine Learning | Scikit-learn LightGBM XGBoost Random Forest TensorFlow Keras CNN |
| Frontend Frameworks | React.js React Native HTML5 CSS3 |
| Backend Frameworks | Spring Boot Flask Node.js Express.js |
| Databases | MongoDB Atlas MySQL Microsoft SQL Server |
| Tools & DevOps | Git GitHub Docker Jupyter Notebook VS Code IntelliJ Figma Roboflow |
- Overview: Enterprise AI recruitment platform built to orchestrate automated technical screening.
- Tech Stack:
CrewAIGoogle GeminiPythonReact - Key Work: Created a multi-agent interview framework to read CVs, dynamically ask adaptive questions, and output analytical evaluation sheets.
- Overview: Context-aware virtual student assistant minimizing university query friction.
- Tech Stack:
React NativeNode.jsGoogle GeminiMongoDBVector Search - Key Work: Built a semantic search ecosystem using Retrieval-Augmented Generation (RAG) to serve real-time document search results.
- Overview: Full-stack machine learning engine tracking cardiovascular risks.
- Tech Stack:
PythonLightGBMFlaskSpring BootReact - Key Work: Cleaned, handled outliers, and feature-engineered over 70,000 health patient records; deployed the pipeline using a decoupled microservices design.
- Overview: Deep learning computer vision application classifying crop anomalies from raw leaf imagery.
- Tech Stack:
PythonTensorFlowKerasStreamlitNumPyPIL - Key Work: Designed and trained a custom Convolutional Neural Network (CNN) architecture across an 87,000+ image dataset to execute 38-class real-time inference via an interactive Streamlit UI.
- Overview: Full-featured enterprise stock tracking and predictive asset system handling resource operations.
- Tech Stack:
Java 17Spring Boot 3Spring MVCApache MavenJSPLombok - Key Work: Engineered a modular Spring MVC backend featuring dynamic item expiry monitoring via customized Merge Sort pipelines, integrated tracking, low-stock threshold dashboards, and isolated file-based storage patterns.
- Dean's List Award (4 consecutive semesters) β Issued by SLIIT for maintaining a consistent 4.00 GPA performance.
- lablab.ai Builder Bronze Badge β Earned by launching TalentCore AI during the AMD Developer Hackathon.
- CodeJam Project Chronos Finalist β Selected to compete in the final round of a high-pressure software engineering sprint.
- AIESEC in SLIIT & Mozilla Campus Club β Active leadership roles driving customer experience, corporate partnerships, and open-source web literacy.
- β‘ Core Focus: Multi-Agent AI, Predictive Modeling, and RAG Pipeline Engineering
- π Hackathons: Completed AMD Developer Act II (Earned Bronze Builder Badge)
- π Communities: Active open-source advocate and Mozilla Campus Club Member
- βοΈ Workflow: Fully automated CI/CD deployments and modular full-stack architectures
π§ Email: mevinimunaweera@gmail.com Β Β |Β Β πΌ LinkedIn: ://linkedin.com
*Feel free to explore my repositories or reach out for collaboration on AI, Data Science, or Full-Stack projects!*