About
Hey! I'm Brian; cs grad from University of Toronto. I'm interested in ml-inference and LLM optimization.
My focus spans low level serving performance and distributing training and vLLM benchmarking to memory bandwidth efficiency and cluster scale compute utilization.
Technical Skills
Languages
- Python (OOP, multithreading)
- C / C++
- Java
- JavaScript
- SQL
- HTML / CSS
Frameworks & Tools
- React, Next.js
- Express, Node.js
- Git, Docker
- REST APIs
- Linux, XML
Specialties
- Deep Learning Inference
- Latency Optimization
- Distributed Systems
- Linear Programming
- Network Security
Selected Projects
Adaptive LLM Inference Engine
600+ tok/s · P99 <3s · 32 concurrent
vLLM
CUDA
Python
Prometheus
Docker
MiniLLM — Pretraining & Kernel Work
Flash Attention 2 · DDP · FSDP
PyTorch
Triton
CUDA
NCCL
Python
Experience
2026
Linkedin
training model
2025
University of Toronto
Architected end-to-end ML pipeline observability using Prometheus and Grafana for platform serving 100k+ concurrent users
2023
RBC Capital Markets
QTS team:Developed latency optimization tools for trading infrastructure using stochastic modeling and data-driven analytics.
2019–2020
IBM
Watson Order Management
Teaching
Teaching Assistant
University of Toronto
2023–2025
- CSC373 — Algorithm Design, Analysis & Complexity
- CSC384 — Introduction to Artificial Intelligence
- CSC2209 — Network Topology (Graduate)
Education
Bachelor of Science in Computer Science
University of Toronto · Class of 2025
Specialization: ML & Systems