AI-focused Computer Science student at the University of Malaya, building production-style software systems across AI, web, backend, and data-driven applications.

• Bachelor of Computer Science student majoring in Artificial Intelligence at the University of Malaya.
• Interested in AI engineering, backend systems, algorithms, and practical product development.
• Focused on building systems that are deployable, maintainable, and useful beyond coursework.
• Currently improving real-world engineering depth through full-stack, data-driven, and AI-assisted products.

An AI-assisted receipt extraction workflow that turns a receipt image into structured fields for human review.

• Tech stack: Next.js App Router, TypeScript, Tailwind CSS, Gemini Vision API, server-side route handlers.
• What I implemented: Image upload validation, server-side AI extraction endpoint, structured JSON parsing, editable review form, raw model-output preview, and local browser persistence.
• Why it matters technically: Shows practical AI automation with a server boundary for API keys, defensive parsing, and a human-in-the-loop review step instead of blindly trusting model output.

An Android and Flutter add-to-app client for IoT water quality monitoring, pollution reporting, and community discussion.

• Tech stack: Java, Android SDK, Retrofit, OkHttp, Bluetooth RFCOMM/SPP, Google Maps, Flutter, Provider, fl_chart.
• What I implemented: Mobile dashboard screens, Bluetooth sensor ingestion flow, REST API integration, JWT request interceptor, GPS-based report flow, charting, and Flutter dashboard module.
• Why it matters technically: Demonstrates mobile engineering beyond CRUD: sensor data handling, API client design, authentication flow, location features, and multi-platform UI work.

An Oracle SQL database system for restaurant order processing, billing validation, and operational reporting.

• Tech stack: Oracle SQL, PL/SQL triggers, sequences, constraints, views, relational schema design.
• What I implemented: Normalized schema, order-detail relationships, validation constraints, compound triggers for order-total recalculation, seed data, and reporting queries.
• Why it matters technically: Shows database design fundamentals, transaction integrity, and business-rule enforcement at the data layer.

A structured repository for implementing and reviewing core algorithmic techniques in Python.

• Tech stack: Python, sorting algorithms, searching foundations, complexity analysis notes.
• What I implemented: Python implementations of classic sorting algorithms and organized lab/tutorial work for algorithm practice.
• Why it matters technically: Supports the CS fundamentals expected for software engineering interviews: decomposition, correctness reasoning, and time/space complexity.

• Languages: TypeScript, JavaScript, Java, Python, SQL, Dart
• Web & App: Next.js, React, Vite, Tailwind CSS, Flutter, Android
• Backend & Data: Supabase, PostgreSQL concepts, Oracle SQL, REST APIs, authentication, database design
• AI / ML: AI-assisted extraction, prompt design for structured output, regression modeling, data preprocessing
• CS Foundations: Data structures, algorithms, sorting, complexity analysis, relational modeling

• Building production-quality student and community software with clearer architecture, documentation, and deployment paths.
• Strengthening backend, cloud, database, and AI engineering fundamentals through applied projects.
• Preparing for software engineering and AI engineering internships in Malaysia, especially Kuala Lumpur.

• GitHub: @Jason421412
• Email: jason421412@gmail.com
• Live demo: Receipt AI Autofill