3rd place · 2025

8th APAC HPC-AI Competition

NSCC Singapore · NCI · Firmus

1st place · 2025

UniHack 2025

Australia’s largest student hackathon

Less is More: Optimising SGLang Distributed DeepSeek-R1 Inference on a Two-Node H200 Cluster

Paper, first author with Nathan Culshaw · ICPP 2026

• Venue. Accepted at Benchmarking in the Data Center (BID ’26), a workshop of the 55th International Conference on Parallel Processing. To appear in the ACM Digital Library.
• Result. Keeping collectives on NVLink and replicating within a node beats sharding across InfiniBand: 17,417 tok/s, 81% over the 16-GPU baseline.

Presenting Less is More at BID ’26

Talk · Singapore, September 2026

• Session. Alongside speakers from NVIDIA and the HPC-AI Advisory Council.

Accelerating the Future: Overcoming Bottlenecks in GPU-Based AI and HPC

Panellist, with NVIDIA and the HPC-AI Advisory Council · ICPP 2026

EvryStay

Founding and Lead Engineer · Dec 2025 to Present

• Built the product from zero. Joined as the first and only engineer. Designed and built Eve, an AI concierge that handles guest conversations end to end for short-term rental hosts, property managers and hotels, along with the property management system integrations and AI service architecture underneath it.
• Fundraise. The platform I built was the product investors backed: EvryStay raised A$4.5M at a A$17M post-money valuation, opening and closing the round inside a week.
• Grew the team. Hired and now lead five full-time engineers in person. I own the architecture, the AI service boundary, code review and the final technical call, while still shipping daily: 300+ merged PRs in my first seven months.

Monash DeepNeuron & Monash eResearch

Lead AI Researcher, APAC HPC-AI Competition Team · Mar 2025 to Nov 2025

• The problem. Maximise inference throughput for DeepSeek-R1 (671B parameters, 37B active) across two 8×H200 nodes, using infrastructure from NSCC Singapore, NCI Australia and Firmus.
• What I found. Fewer GPUs arranged deliberately beat more GPUs arranged by default: a tuned single node (PP2 · TP4 · DP4 attention) hit 17,417 tok/s at 2.05× the per-GPU efficiency of 16 GPUs. The boring stuff mattered most: CUDA version alignment alone was worth +35%, and 40+ hand-tuned NCCL configs never beat the defaults.
• Outcome. Presented on stage at SupercomputingAsia 2026 in Osaka. The work became the ICPP paper.

Monash DeepNeuron

AI & HPC Technical Team, Outreach · Feb 2025 to Present

• Research. Neural Cellular Automata for modelling self-organising biological systems (see Selected Projects).
• Outreach. Ran hands-on workshops in Victorian high schools on how deep learning models work and how to use generative AI well.

Freelance AI Engineer

Scag Australia, International Mowers · Jan 2025 to Nov 2025

• Customer-facing AI agents. Built the Scag Mechanic and IM Advisor assistants for model comparison, troubleshooting and service recommendations. Structured proprietary product data, shipped embeddable chat widgets for web and mobile, and put brand persona and legal guardrails around both.

EvryStay’s company agent, lives in Slack · 2026

• What it does. Describe a feature in a Slack thread and Dummy builds a working version: real branches across three repos, a seeded full-stack preview at a permanent URL, desktop and mobile QA screenshots, and draft PRs.
• Why. So the non-technical side of the company can see their ideas working before engineers spend time on them.
• Guardrails. An independent review agent checks the code, sensitive changes need an allowlisted human to approve in Slack, and nothing it does can merge, deploy or touch production. Built on the open source QM harness.

UniHack 2025 winner, team of six · 2025

• What it is. Habit tracking as a garden you grow by getting things done. 1st of 135+ projects at Australia’s largest student hackathon.
• My part. Architected the AI assistant in Langflow (contextual chaining, no fine-tuning), built the DataStax data model and live sync, and led the pitch to the judges.

Monash DeepNeuron research, live at neuralca.org · 2025 to Present

• What it is. Models that grow complex patterns from local rules, including a 3D NCA trained on time-resolved mouse embryo data to explore gastrulation-like development.
• What I built. The 3D temporal training path—reduced data and voxel handling, dynamic frame-to-frame batches, differentiable IoU and loss instrumentation—plus PyTorch models and browser inference work.

Open experiment record behind the ICPP paper · 2025

• What’s in it. Launch scripts, Slurm logs and workbooks for every configuration tried across two 8×H200 nodes.
• Why it matters. Every number in the paper can be reproduced from it.

Chrome extension

• What it does. Privacy-focused extension that remembers your exact scroll position on any webpage.