selected projects
systems, ai, and product work
Compact notes on the work that best reflects how I think: system design, technical depth, and useful products.
ai infrastructure
Durable AI Agent Workflow Platform
A production-style platform that runs AI tasks as durable workflows. Hand-built execution engine
with commit-before-execute steps, retry/backoff, idempotency keys for effectively-once side effects,
and a crash-recovery sweeper. Adds human-in-the-loop approval gates, OpenTelemetry tracing to Jaeger,
a cost/latency dashboard, and an automated eval harness across a benchmark suite.
FastAPICeleryPostgresRedisOpenTelemetryNext.js
github
ai systems / language models
GPT-2 from Scratch with LoRA + Speculative Decoding
A 124M GPT-2 built from scratch in PyTorch and taken end-to-end. Pretrained on 10B tokens of FineWeb-Edu
across 4x A100 on Modal (val loss 3.30), then validated against OpenAI's GPT-2 on HellaSwag - 0.295 vs 0.311
acc_norm on the same harness. Adds LoRA fine-tuning with downstream benchmarks (SST-2 79.7%, E2E-NLG BLEU
21.6), a KV cache, and speculative decoding proven distributionally exact against plain sampling.
PythonPyTorchModalDDPLoRATransformers
github
agentic ai
Work Buddy - Workstream Control Agent
A multi-agent system (Google ADK) that turns messy project context - meeting notes, Slack, Jira, repo state -
into an auditable execution ledger. Specialist sub-agents extract tasks, decisions, and blockers, reconcile
duplicates across sources, and draft Jira/Slack/PR/email updates, with a human-in-the-loop approval gate before
any external write, secret redaction throughout, and the same tools exposed over an MCP server. Built for the
Google & Kaggle AI Agents Intensive capstone.
Google ADKMulti-AgentMCPGeminiFastAPI
github
video classification / 2019
Violent Crowd Behaviour Detection
Trained a C3D model on the ViolentFlow dataset to classify violent versus non-violent behaviour in crowd
footage. The work was written up and published as a paper.
C3DVideoViolentFlowPublished
github
computer vision / 2019
Galaxy Zoo Morphology Classification
Final-year bachelor's project comparing convolutional architectures on the Galaxy Zoo dataset to pick the
most suitable model for galaxy morphology classification. Published as a paper.
CNNAstronomyClassificationPublished
github