Professional Summary

Full-stack & data-platform engineer with production LLM UX, scalable search/data systems, and quantitative research. Built a real-time React (TypeScript), FastAPI, and WebSockets chat that streams tokens from multiple LLM providers. Engineered equities pipelines with Python and scikit-learn using regime clustering that reduced backtest max drawdown by 77.7%. Operated multi-region Kubernetes services to 99.9% uptime and accelerated Elasticsearch queries by 50% after migrating from MongoDB.

3+

Years Experience

4

Companies

18+

Technologies

2

Research Papers

Professional Experience

Software Developer

Kolo AI | Pasadena, CA | Jun 2024 – May 2025; Sep 2025 – Present

  • Built a persona-driven chat UI in React and TypeScript with streamed Markdown and inline citations; added icons/tooltips and model defaults so users can reliably control tone/behavior.
  • Shipped Google Calendar integration end-to-end (OAuth 2.0 PKCE, create/read, webhook-driven sync) with concurrency-safe handlers and idempotency to prevent duplicate events.
  • Implemented a usage & cost attribution pipeline across Sendbird/Telnyx with Decimal-safe accounting, timezone-correct aggregation, webhook ingestion, and SQL/Grafana dashboards.
  • Prototyped a menu-intelligence data pipeline: multithreaded/recursive crawling, image/PDF extraction, LLM-assisted cleaning, and APIs powering a restaurant-recommendation chat flow.
  • Delivered core frontend features for mobile/desktop (new-conversation flow, auth, settings/sidebar, layout polish) and added moderation profiles (SHAFT) to switch safety modes per session.

Quantitative Analyst Intern

Draco Evolution | Taipei, Taiwan | May 2025 – Aug 2025

  • Built a real-time intraday research stack that streamed tick/minute data from Polygon.io and executed paper trades on Alpaca; computed features and ran in-process inference for 5-second signals.
  • Engineered a Python ML pipeline with scikit-learn (StandardScaler, SelectKBest[f_regression], HistGradientBoostingRegressor), plus PCA with K-Medoids regime clustering.
  • Designed leak-free, walk-forward backtests tracking P&L, win rate, cumulative P&L, and max drawdown; delivered 77.7% lower max drawdown than buy-and-hold and identified regimes with 54% up-move and 54% down-move clusters.
  • Ensured market-aware data handling by aligning to exchange sessions and maintaining incrementally updated historical datasets from Polygon REST, enabling reproducible forward tests.

Software Engineer Intern

TSMC | Taichung, Taiwan | Jun 2024 – Aug 2024

  • Operated fab-support services on Kubernetes across Taiwan, Germany, and Japan, instrumented with Prometheus and Grafana, delivering 99.9% uptime for internal users.
  • Migrated fab-floor ticketing data from MongoDB to Elasticsearch, tuning index/shard layout and mappings to enable semantic-style queries and 50% faster search latency.
  • Extended the backend in Java to support role-based submission, cross-department routing, and export features; deployed updated services via kubectl and Kubernetes manifests.

Research Analyst

University of Cambridge, Centre for Alternative Finance | Cambridge, UK | Feb 2022 – Apr 2023

Education

Bachelor of Science in Computer Science

University of Southern California | Los Angeles, CA | Aug 2021 – Present

GPA: 3.41 · Upper-Division CS GPA: 3.56

Technical Skills

Languages & Frameworks

PythonC++CJavaScript/TypeScriptSQLJavaHTML/CSSSpring BootFastAPIDjangoFlaskReact.jsStripe

Tools & Technologies

GitDockerKubernetesAWSMySQLMongoDBElasticsearchpandasscikit-learnTensorFlowPyTorchKerasHugging Face

Languages

English

Fluent

Chinese

Fluent

Contact