Jay Ree

AI-Powered Personal Executive Assistant for Productivity & Time Management

• Led the end-to-end architecture and development of a full-stack AI assistant platform — building the backend in Node.js (Express) with Supabase (PostgreSQL) and the mobile client in Flutter (iOS) — integrating third-party services including Google Calendar, Notion, and Google Cloud voice APIs to deliver a unified productivity tool.
• Owned the AI feature pipeline, designing a conversational assistant using Google Gemini that autonomously manages calendar scheduling, task prioritisation, and personalised recommendations through long-term memory of user preferences.
• Directed technical strategy and sprint planning across frontend and backend teams, driving code reviews, API design decisions, and release cycles while coordinating cross-functional collaboration between developers and designers.

Dynamic Platoon Formation of Multi-Type Autonomous Vehicles for Sustainable Urban Mobility

• Co-authored an IEEE ITSC-targeted research paper with Dr. Mohammed Eunus Ali, introducing a novel system where smaller Passive Vehicles (PVs) are physically towed by larger Active Vehicles (AVs) on shared highway segments, formulating the platoon formation problem as a constrained optimisation model with multi-segment matching and point-wise capacity constraints.
• Designed and implemented two matching algorithms — a Greedy Maximum-Weight Matching baseline and an Iterative Linear Assignment (ILA) method using the Jonker–Volgenant solver — achieving 25–52% energy-proportional distance coverage across synthetic scenarios with up to 400 PVs and 80 AVs.
• Built an end-to-end experimental framework in Python (NumPy, SciPy, Pandas, Matplotlib) with parameter sweep experiments, automated data pipelines, and comparative visualisation tools for algorithm benchmarking.

• Built core features for an AI-powered job application SaaS, including resume–job matching and automated application workflows using React, TypeScript, and Firebase.
• Improved deployment reliability by setting up CI/CD with GitHub Actions and Husky.
• Integrated RESTful APIs and optimised database queries for better scalability.

• Coordinated hardware lifecycle management across multiple Coles Divisions, ensuring smooth deployments, upgrades, and resolution of hardware-software integration issues across functional teams.
• Automated manual reporting processes using VBA (Microsoft Macro), reducing processing time from 4 hours to 30 minutes, streamlining asset tracking and improving data accuracy across the team.
• Optimised vendor management and asset processes, securing cost-saving agreements and contributing to over $90,000 in operational savings through lifecycle planning.

• GPA: 3.769 / 4.000 (High Distinction)
• 2023 & 2024 Monash Engineering Dean’s Honours recipient (Top 3% of engineering students)
• Working proficiency in Python, Java, TypeScript/JavaScript, Tailwind CSS, MongoDB, SQL, and PHP for software development; strong understanding of algorithms, data structures, and databases.
• Experienced with Linux, Angular, React, Meteor, Firebase, and Git. Industry experience developing Microsoft Excel Macros for system automation and debugging hardware using measurement tools.

• Graduated with GPA of 4.0 / 4.0 (High Distinction)
• Recipient: Engineering International Undergraduate Excellence Scholarship (awarded for ATAR equivalent >96 and exceptional academic performance)