Turning data into decisions.
Where rigorous Math meets applied AI and Data Science.
I'm a fourth-year Mathematics student at UBC building toward a career at the intersection of generative AI and data science. My interests sit where rigorous analysis meets practical AI systems: turning messy data into clear decisions, and building tools that put language models to work on real problems.
What I bring to the table.
The tools and disciplines I reach for on every build.
AI
Generative AI, LLMs, RAG pipelines, machine learning.
Data Science
Statistical modeling, experimentation, data analysis.
Data & BI Tools
Power BI, PostgreSQL, OracleDB, Excel, HubSpot.
Languages
Python, SQL, R, JavaScript, C++, Java, C#.
Cloud & GenAI
AWS fundamentals, LLM concepts, RAG pipelines.
Data Libraries
Pandas, NumPy, Scikit-learn, Plotly, Matplotlib.
Backend & Web
Node.js, Express, REST APIs, HTML/CSS.
DevOps & Tools
Git, GitHub, Docker, CI/CD, Jira.
Certified, and still learning.
A running list of credentials I've earned, with a couple still in progress.
Things I've built.
A few projects that show how I think and build.
Notes & write-ups.
Everything I write gets filed into one of three categories.