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Wenfeng Pan

Production Engineer

Facebook

Hey, I’m Wenfeng!

Nice to meet you!

🎙️ 👨‍🍳 🎮 🎦

Interests

  • Software Development
  • Site Reliability Engineering
  • Systems engineering
  • DevOps engineering

Education

  • Master of Computer Science, 2018

    University at Buffalo

  • Bachelor of Software Engineering, 2014

    Qingdao University

Skills

Python + Django

Java + Spring

Linux / Unix

Docker / Kubernetes

PostgreSQL / MongoDB

RabbitMQ / Redis

Vue.js / React

Amazon Web Services

Microservices

Experience

 
 
 
 
 

Production Engineer

Facebook

Mar 2020 – Present Menlo Park, CA
 
 
 
 
 

Systems Engineer

Electronic Arts

May 2019 – Aug 2019 Austin, TX
Responsibilities include:

  • Built a delivery request tool using Python, Django, Flask, React and MongoDB, which integrated with automation tools and simplified the process of infrastructure deployment
  • Implemented microservices architecture using RabbitMQ Publish–subscribe pattern to expedite the process of building game servers
  • Assembled every component in the microservices as docker container, which supported rapid development and testing through continuous integration and deployment in GitLab
 
 
 
 
 

Software Engineer Intern

ifanr Inc.

Mar 2018 – Aug 2018 Guangzhou, China
Responsibilities include:

  • Participated development of a BaaS Serverless Platform similar to AWS Lambda, which provided high-quality services for 50,000 developers and 80,000 applications every day
  • Changed the basic authorization to Single Sign On (SSO), which reduced 15% server load
  • Used Python to maintain an old version Twitter Bot, which published article automatically

Projects

Amazon Dynamo Style Key-value Store

Amazon Jan 2019
Implemented distributed storage system using Android application, supported basic object actions and membership maintenance; Implemented a cycle replication system for key-value partitioning using SHA-1 function; Designed object versioning system and used Merkel tree for resynchronization after failures; Satisfied consistency and availability of CAP theorem for all clients in the system

FaceRank

Labs May 2017
A project can extract facial landmark and evaluate the beauty of face, which is inspired by a book Computer Models for Facial Beauty Analysis; This project use The Vertical Thirds and Horizontal Fifths algorithm to evaluate the beauty of the photos

Beijing Housing Price Prediction

Labs Jan 2017
Showed data virtualization by Pandas, NumPy, matplotlib, and displayed the performance of the decision tree; Input 10,000 groups data of housing price as a practice, and achieved 78.92% model performance

Raspberry Pi Live Streaming

Labs Dec 2016
Implemented the online streaming system with Node.js, WebSocket and FFmpeg; Used Raspberry Pi as server, support for streaming up to 100 clients