Welcome to my GitHub profile!
-
🎓 Education:
- BASc in Computer Engineering at the University of British Columbia
-
💡 Technical Interests:
- 🚀 Machine Learning: Designing efficient pipelines, running large-scale distributed training, and exploring model optimization techniques.
- ☁️ Cloud Computing: Building scalable and sustainable cloud infrastructures, with a focus on carbon-aware systems.
- 🔗 Distributed Systems: Implementing fault-tolerant systems, and exploring scalable database design.
- 🕸️ Software Engineer Intern at Rippling
- Developed an event-matching algorithm to detect missing events, scanning 6k+ events/hour.
- Designed a Kafka event producer for bulk database transactions, reducing infra costs by $216k annually.
- 🏦 Quantitative Developer Intern at Squarepoint Capital
- Built end-to-end automated solution for anomaly detection and cleaning of historical data.
- Developed a real-time Streamlit dashboard for monitoring data quality.
- 🤖 Machine Learning Engineer Intern at RBC Borealis AI
- Developed back-end services for ML models using FastAPI and PostgreSQL.
- Implemented monitoring dashboards with Grafana and custom metrics using Prometheus.
- Designed a generic training pipeline using Dagster, dbt, and ClickHouse.
- 🌱 Research Assistant at UBC Cloud and Infrastructure Lab
- Worked on Caribou, a project to reduce the carbon footprint of serverless applications.
- Built a non-linear optimizer for UnFaasener, to reduce serverless billing costs.
- 🌐 Prev Intern @ Arista Networks and NETINT Technologies
- 🔍 StudyBuddy: A messaging app built with Node.js and MongoDB, featuring live chat, and a RAG-based study assistant powered by ChromaDB and ChatGPT-3.5
- 🗺️ MapReduce in Go: Implemented a simplified version of MapReduce inspired by the Google MapReduce paper.
- 📦 Distributed Key-Value Store: Developed a CRUD-capable key-value store in Java using gRPC and Protobuf.
- 🔒 OS/161 Kernel Build: Built synchronization primitives, system calls, and virtual memory systems from scratch.
- 🚀 Machine Learning Pipelines & Optimized Systems for AI Workloads
- 🖥️ Building sustainable, carbon-aware infrastructure
- 📊 Balancing performance trade-offs in distributed systems
✨ Let's build something awesome together! ✨