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starrdye/README.md

Hi, I'm Xingye (Zhou Xingye) πŸ‘‹

CS student at National University of Singapore with a thing for building tools that are actually useful β€” and occasionally, writing code just to see what happens.

Currently a Fund Operations and AI Engineer Intern at Ternary Fund Management, where I also build the software that powers the fund's factsheet pipeline and internal tooling.


What I'm working on

  • Workable β€” A personal workflow engine that uses AI to turn a plain-English description of how you work into an interactive process graph. It identifies nodes, roles, and directed edges automatically, groups steps into named phases, flags bottlenecks and single points of failure, and lets you toggle between your current workflow and an AI-optimised overlay β€” non-destructively. Supports Claude, Gemini, and Doubao. Built with Next.js, React 19, and TypeScript. Live at workable-demo.tooboss.com.
  • Gravion β€” My own quant terminal for scanning NASDAQ 100 stocks using MA crossover + earnings growth signals, built on top of the Moomoo OpenD API.
  • Cipres β€” A privacy-first BI dashboard that transforms raw operational data into professional, print-ready reports entirely in the browser β€” no sensitive data ever leaves your machine. Powered by smart AI-driven data ingestion, customisable charting, and a self-correcting audit layer that traces every number back to its source.
  • Mood Notes β€” A mood tracking app to log daily emotions and reflect on patterns over time.

A bit about me

I'm a genuine tech lover β€” not just someone who codes for a living, but someone who gets genuinely excited watching technology change the world in real, tangible ways.

My hands-on experience with AI and machine learning spans both ends of the stack:

  • At Panasonic, I architected a real-time computer vision pipeline using OpenCV and YOLO to detect distorted QR codes in industrial environments
  • At GIC (Singapore's sovereign wealth fund), I worked on data ingestion pipelines as part of their SPO division, giving me an early look at how institutions handle data at scale

Beyond traditional finance, I've assisted with the setup of a few Web3 fund structures β€” getting firsthand exposure to how decentralised infrastructure intersects with institutional capital.

Right now, my biggest obsession is the question: how do AI and Web3 transform finance? Whether it's automating the analyst's workflow, making fund reporting instant and auditable, or rethinking how capital flows in a decentralised world β€” that's the space I want to build in.


Tech I reach for

Languages TypeScript Python Go Java C++ Node.js

Frontend React Next.js React Native Expo

Backend & APIs Express REST WebSockets

Databases PostgreSQL MongoDB Redis SQLite

AI / ML OpenCV YOLO PyTorch LangChain Claude API Gemini API

Infra & Tools Docker Git GitHub Actions Electron

Pinned Loading

  1. lynx-project lynx-project Public

    Stop re-prompting your AI: A mobile AI agent with persistent, project-based memory for seamless cross-session continuity. #TechJam 2025

    TypeScript 1

  2. csd-solver csd-solver Public

    Simulates colour vision deficiencies (Protanopia etc.) on images using daltonlens + Brettel 1997 model β€” for accessibility testing and UI design

    Python

  3. mood-notes mood-notes Public

    The cute mood tracker β€” capture feelings in a simple, private & organized space, with a FlipBook journal, animated mood faces, and 100% local storage. Built with Expo & React Native.

    TypeScript

  4. cipres cipres Public

    TypeScript

  5. gravion gravion Public

    Desktop quant terminal (Electron + React + Python) scanning NASDAQ 100 for MA crossover + YoY earnings growth signals via Moomoo OpenD API

    TypeScript