Lawrence Qi
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Lawrence Qi

Melbourne, Australia celarry1@gmail.com lawrenceqi.com github.com/rockminelaw

I study Computer Science at Monash University and graduate in October 2026. In November I'm moving to Singapore to start an AI/ML internship at NetGain, working on small language models that run locally.

Experience

  • AI/ML Intern (incoming), NetGain

    Nov 2026 – Feb 2027

    A three-month internship on knowledge distillation and small, locally hosted language models for infrastructure and monitoring workflows.

    • Evaluating open-weight models for log analysis, classification, summarisation, structured extraction and routing.
    • Benchmarking accuracy, latency, memory use and inference cost on CPU-only systems.
    • Testing fine-tuning, LoRA, quantisation, distillation and fallback to larger models for uncertain cases.

  • Academic Tutor, Unitop

    Feb 2023 – present

    One-on-one tutoring for students from grade 1 to grade 9.

    • Raised students' marks by up to 35 percent.
    • Worked with parents and teachers to keep learning plans aligned between home and school.

Projects

  • Valorant live win probability

    Apr 2026 – present

    Python, OpenCV, EasyOCR, XGBoost, LightGBM, River, Docker, Nginx, PostgreSQL. Solo

    • Samples VCT broadcast footage, reads the scores, timer, spike and player panels from the HUD, and splits matches into rounds automatically.
    • Builds features for economy, player advantage, ultimate availability, map state and spike status.
    • Trains gradient-boosted trees on professional matches, targeting 75%+ accuracy.
    • Serves predictions from a Docker container through REST endpoints behind Nginx.

  • Homelab and Kubernetes cluster

    Sep 2025 – present

    Proxmox, Kubernetes, Docker, Linux, Nginx, Cloudflare. Solo

    • Combined compute across several machines into one cluster for containerised workloads.
    • Runs Jellyfin, databases, reverse proxies and my own apps, with selected services exposed through Nginx, Cloudflare DNS and HTTPS.
    • Fixed storage and networking issues that took large-file transfers from about 10 MB/s to 70 MB/s.

  • AI email assistant

    Mar 2026 – present

    Chrome Extension API, JavaScript, Node.js, Python, OpenAI API, SQLite. 5-person team

    • Built an LLM pipeline for classification, priority detection, thread summaries and reply drafts.
    • Designed a human-in-the-loop approval step so AI-written replies can't go out without confirmation.
    • Interviewed people at large organisations and turned their feedback into requirements.

  • Autonomous shopping cart

    Mar 2025

    C++, Arduino, RFID. UNIHACK 2025, 5-person team

    • Wrote the A* pathfinding that modelled the store layout and found the shortest route between items.
    • Added real-time obstacle avoidance based on the Dynamic Window Approach and Velocity Obstacles, so the cart reroutes around people.
    • Integrated motors, sensors and the Arduino with the rest of the team's software into a working prototype.

Education

  • Bachelor of Computer Science, Monash University

    Graduating Oct 2026

Skills

Machine learning
Python, PyTorch, NumPy, Pandas, XGBoost, R, LoRA and QLoRA fine-tuning
Infrastructure
Docker, Kubernetes, Proxmox, Linux, Nginx, Cloudflare, AWS, Azure
Software
JavaScript, TypeScript, HTML and CSS, Java, SQL, Git
Languages
English, Mandarin, Cantonese, French