RAG System for Open Access to Court Cases
PresentDeveloping advanced embedding strategies and relationship modeling to improve legal information retrieval for 100M+ court cases, aimed at bridging the justice gap for self-represented individuals.
About Me
Hello! I’m currently a Master's student in Big Data at Simon Fraser University. I obtained my Bachelor's degree in Mathematics with a double major in Statistics and Computational Mathematics from the University of Waterloo.
Focused on end-to-end ML systems, my expertise spans from Data Science to MLOps to build, deploy, and scale high-impact AI solutions. Beyond my core studies, I’m a researcher at heart—deep-diving into NLP and Computer Vision to stay at the forefront of AI innovation.
In my free time I enjoy playing badminton a lot. My favorite animal is cheetah and blue sharks are my favorite sharks (greenland sharks are pretty cool too).
Projects
Developing advanced embedding strategies and relationship modeling to improve legal information retrieval for 100M+ court cases, aimed at bridging the justice gap for self-represented individuals.
Led a team of 4
Built a ML-driven portfolio optimizer (Nested Clustered Optimization) with an interactive UI that generates allocations based on tickers and risk targets.
Led a team of 4
Delivered LLM + NLP pipeline that filtered 9K+ customer reviews, performed sentiment scoring, and surfaced pain-point topics to guide product improvements.
Explored global drivers of music virality with ETL, feature engineering, modeling, and visualizations to explain popularity shifts.
Work Experience
May 2025 — Present
Multi-Domain AI Development: Engineered end-to-end solutions across NLP, Computer Vision, and Statistical Machine Learning, specializing in the deployment of scalable models for industrial applications.
Full-Stack MLOps Engineering: Bridged the transition of research prototypes into production-ready AI services, implementing robust data pipelines to handle multi-modal inputs including imagery, unstructured text, and spatial data.
Innovation: Search and prototyped cutting-edge academic research methods to solve industrial challenges.
Sep 2025 — Dec 2025
Guided graduate labs on Hadoop, Spark, NoSQL, and scalable data pipelines; unblocked debugging and reinforced best practices for distributed systems.
Jun 2023 — Jul 2023
Cleaned and transformed 30+ datasets (1M+ rows) in SQL; built a BI dashboard to flag high-risk customer groups and alert key metrics in real time.
Education
09/2024 — 04/2026
09/2021 — 08/2024