ppaanngggg

Frontend Developer

https://talent.gravityer.com/ppaanngggg

Shanghai, Shanghai, ChinaMember since June 22, 2026

Key Strengths

Demonstrated proficiency in Python, TypeScript, and JavaScript through various personal projects.
Experience with Dockerfile indicates familiarity with containerization.
Exposure to machine learning and deep learning frameworks (LayoutLMv3, YOLO, DeepRL) suggests analytical and problem-solving capabilities.
Frontend-related technologies like TypeScript, JavaScript, and CSS are present in personal projects like 'token-counter' and 'design0'.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project portfolio is diverse, covering areas from machine learning and quantitative trading to web tools. This breadth suggests adaptability and a willingness to explore different technical domains. The personal nature of all projects indicates self-motivation and initiative. While the projects demonstrate a wide range of technical interests, the direct alignment with a dedicated 'Frontend Developer' role is moderate, as many projects lean towards backend, data science, or C++ development. However, the presence of TypeScript, JavaScript, and CSS in some projects does show an interest in frontend technologies.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

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Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

design0

October 31, 2024 – April 3, 2025

Effortless Design for Everyone

View Project

yolo-doclaynet

May 13, 2024 – Present

YOLO models trained by DocLayNet - power your Document Intelligent by Layout Analysis

View Project

token-counter

April 24, 2024 – December 5, 2025

Now Part of Price Per Token. Web tool to count LLM tokens (GPT, Claude, Llama, ...)

View Project

layoutreader

March 5, 2024 – August 15, 2025

A Faster LayoutReader Model based on LayoutLMv3, Sort OCR bboxes to reading order.

View Project

finviz-proxy

August 2, 2023 – December 21, 2024

Unoffical APT for Finviz screener application

View Project

ParadoxTrading

January 14, 2018 – July 13, 2018

Flexible quantitative trading framework

View Project

PyCTP

June 9, 2017 – March 12, 2018

PyCTP — repository

View Project

DeepRL

June 29, 2016 – July 7, 2018

Framework for deep reinforcement learning.

View Project

KCFTracker

August 20, 2015 – October 30, 2015

KCFTracker for opencv2

View Project

fhog

August 7, 2015 – September 17, 2015

fhog — repository

View Project

Key Strengths

Demonstrated proficiency in Python, TypeScript, and JavaScript through various personal projects.
Experience with Dockerfile indicates familiarity with containerization.
Exposure to machine learning and deep learning frameworks (LayoutLMv3, YOLO, DeepRL) suggests analytical and problem-solving capabilities.
Frontend-related technologies like TypeScript, JavaScript, and CSS are present in personal projects like 'token-counter' and 'design0'.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

ppaanngggg

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit