I'm a Computer Science and Statistics (Machine Learning Stream) student at the University of Toronto graduating in 2027. I love to build ML/AI systems that scale. At RBC, I built a RAG pipeline set to serve 1000+ users and deployed a risk-classification ML pipeline processing millions of data daily.
Currently: ML Engineer Intern @ Shopify (Search Relevance)
🌐 joshuacrisologo.com · 💼 LinkedIn · 🏆 Devpost
| Project | Description |
|---|---|
| Realtime ML Network Intrusion | Real-time intrusion detection: benchmarked 4 ML models on 163K+ flows (UNSW-NB15), then served XGBoost from C++ via ONNX over a Kafka pipeline: 4.2M pkts/s parse, 90K flows/s inference |
| Hemgjord | Full-stack 3D room design app — async rendering pipeline handling ~500 req/s on GCP |
| Relay | AI memory layer that captures the why behind merged PRs (Cerebras) and flags conflicting decisions in a Backboard knowledge graph; queryable by devs & AI agents |
| PromptPilot | Chrome extension that optimizes LLM prompts using few-shot & chain-of-thought techniques |
| Curator's Companion | Android app for the Toronto Asian Art Museum managing 100+ records in real-time |
| MAMA Dashboard | 🏆 Best Insights — Tableau dashboard for UN SDG maternal mortality data |