/* As a sophomore pursuing a Bachelor's in Applied Mathematics and Comouter Science, I'm passionate about LLM, VLA and embodied AI */
Explore my work, including turning messy data into structured insights during my externship at Breaking Games.
✅ Verified by Extern
Turn six messy CSVs into an analytics database and a Q4 dashboard that drives real business decisions. SQL + Claude.
DKU Innovation Incubator Phase II -- 2nd Prize, Campus Challenge Cup -- Contributed to risk prediction logic, Python-based data analysis, and user scenario documentation for an AI-driven elderly safety system -- Supported project narrative and presentation materials -- demonstrating interest in real-world, user-centered AI applications. Considered both technical performance and real-world needs, including privacy, caregiver workload, and system usability.
Team Project -- Designed a script-based experience in which users assume the roles of historical figures, receive character-specific information and narrative tasks, and uncover connections among people, events, and library collections as the story progresses. -- Collaborated across content research, narrative design, interface planning, and technical feasibility, learning how to prioritize core features and turn a broad creative idea into a coherent, demonstrable product.
As a sophomore pursuing a Bachelor's in Applied Mathematics and Comouter Science, I'm passionate about LLM, VLA and embodied AI
Physical AI, Embedded AI, Autonomous Intelligent System (Embodied Intelligence), Multimodal
Externships
SQL & Database Architecture Externship with Breaking Games
Completed · Oct 2026
Experience
Data Analytics Extern
Breaking Games · June 2026 -- Present
Private Wealth Management Intern
GF Securities · 2026
Education
duke university
B.S. in Applied Mathematics and Computational Sciences · Class of 2029
Skills
✅ Verified by Extern
Turn six messy CSVs into an analytics database and a Q4 dashboard that drives real business decisions. SQL + Claude.
The externship consolidated six e-commerce CSV sources into a validated SQLite analytics database. Work documented each source schema and gaps, performed ETL and normalization into queryable tables, and produced SQL queries that returned five ad-hoc answers about product performance, catalog size, ad spend, and checkout sessions.
I produced a validated SQLite dataset and a suite of SQL queries that returned five specific answers: top products by units and revenue, catalog size, total Meta ad spend, and unique checkout sessions.
DKU Innovation Incubator Phase II -- 2nd Prize, Campus Challenge Cup -- Contributed to risk prediction logic, Python-based data analysis, and user scenario documentation for an AI-driven elderly safety system -- Supported project narrative and presentation materials -- demonstrating interest in real-world, user-centered AI applications. Considered both technical performance and real-world needs, including privacy, caregiver workload, and system usability.
Team Project -- Designed a script-based experience in which users assume the roles of historical figures, receive character-specific information and narrative tasks, and uncover connections among people, events, and library collections as the story progresses. -- Collaborated across content research, narrative design, interface planning, and technical feasibility, learning how to prioritize core features and turn a broad creative idea into a coherent, demonstrable product.