About

I am a Computer Engineering major at McMaster University. I love problem-solving and have a passion for learning new skills. I am especially interested in C++, high performance computing, concurrency, operating systems, distributed systems, algorithms, and data structures.

I was previously a SWE Intern @ Pure Storage, where I profiled C++ code with Linux Perf to identify bottlenecks. I resolved these bottlenecks with many different optimization techniques such as branchless logic, template meta-programming, loop unrolling, and SIMD/vectorization. Over the course of my internship I was able to increase the throughput of a persistant metadata store by 5.07x (407%). I have also interned at MHI RJ Aviation as a Data Engineer Intern where I optimized ETL pipelines and created data visualizations with Python and Polars.

I am also active in extracurriculars on campus. I am the President of the McMaster Artificial Intelligence Society and a member of the McMaster Competitive Programming Club.

When I am not programming I enjoy working out, listening to music, and spending time with my friends.

Experience

Pure Storage

Software Engineer Intern

May 2025 - August 2025

Worked with the FlashBlade Core Data team to optimize the decompression path of a persistent metadata store.
Profiled the hot path and identified bottlenecks with Linux Perf. Removed bottlenecks with classic HPC techniques such as compile-time calculations, loop unrolling, and vectorization which increased throughput by 407%.
Automated benchmark visualizations with Bash, Python, and matplotlib to save approximately 5 minutes per run.
Developed a robust unit and performance test generation system with C++20 template meta-programming and GoogleTest to validate the bit-level compression and decompression algorithms of the persistent metadata store

MHI RJ Aviation

Data Engineer Intern

May 2024 - April 2025

Optimized 4 ETL Pipelines up to 82% by refactoring from Pandas to Polars and optimizing legacy Python code to Python 3.12 ensuring usage of Python optimization tools such as list comprehensions, generators, and decorators.
Developed 3 full-stack web apps in Python using Dash, Plotly, and Polars to dynamically display sales and backlog data from an SQL database which provided executives with a detailed oversight of $10M+ total monthly revenue

MacAI

President

May 2024 - Present

Led new educational and project initiatives resulting in a record-high 1.3k+ member count.
Developed CNN and neural network demos in Jupyter Notebook using TensorFlow, Keras, sklearn, and matplotlib to further attendees understanding of concepts such as data preprocessing, model validation, and model fine-tuning.

Projects

Redis Server

Implemented two different server architectures - multi-threaded and lock-free event-driven. Compared them in both latency and throughput using Google Benchmark and std::chrono.

GitHub