8000 zoechenry (Zoe Chen) · GitHub
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  • Columbia University
  • New York, NY
  • 20:39 (UTC -04:00)

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zoechenry/README.md

Hi👋, I'm Zoe Chen

  • Effortlessly shifts between world of data and business-senario - that's me!
  • Excited about using data to make a real-world impact.
  • 2 years of industrial experience in leading finance and tech companies.
  • "Your enthusiasm is intimidating everyone🔥" -- as expressed by my friends.
  • Proud owner of a Bichon Frisé named Lucky🐶, passionate about snowboarding🏂, climbing🧗, yoga🧘, and dancing💃.

About Me

Education Background

  • Graduate Data Science Student at Columbia University, NY.
  • Bechelor's degree in Software Engineering from Peking University, CN.
  • Bechelor's degree in Finance from Shanghai University, CN.

Interests

  • Machine Learning
  • Data Science
  • NLP
  • Large Language Models
  • Web3 & Blockchain & Crypto

Projects

AI-Photo-Album-Web-Application link

  • Objective: Developed an intelligent photo album web application with natural language text and voice search for efficient photo collection.

  • Implementation: Front-end development with HTML, CSS, JavaScript; advanced search with AWS Lex, Rekognition; a robust AWS-powered backend with S3, OpenSearch, Lambda, API Gateway; automated deployment with AWS CodePipeline, CloudFormation.

Dining Concierge Chatbot link

  • Objective: Build a Dining Concierge chatbot that sends users restaurant suggestions given a set of preferences that users provide the chatbot with through conversation.

  • Implementation: AWS Lex, AWS services, AWS S3, API Gateway, Swagger, AWS Lambda, DynamoDB, ElasticSearch, SQS, SNS, and CloudWatch.

Smart-Contract-Vulnerability-Detection-Multi-label-Classification-Model link

  • Objective: Created a multi-label classification model designed to detect the 20 vulnerabilities in smart contracts.

  • Implementation: Used Beautiful Soup to scrape data, solidity-parser to parse data, implemented DFS and BFS algorithms to transform data, and developed a BERT model.

Stock-Recommendation link

  • Objective: Designed a stock recommendation system designed to recommend the top-performing stocks to investors on WeChat Mini Program.

  • Implementation: for algorithms, built XGBoost, Random Forest, SVM models to predict stock performance, applied Soft Voting to ensemble the 3 models.

Pinned Loading

  1. AI-Photo-Album-Web-Application AI-Photo-Album-Web-Application Public

    JavaScript

  2. DiningConcierge DiningConcierge Public

    JavaScript

  3. Smart-Contract-Vulnerability-Detection-Multi-label-Classification-Model Smart-Contract-Vulnerability-Detection-Multi-label-Classification-Model Public

    Jupyter Notebook 1 1

  4. Stock-Selection-Model Stock-Selection-Model Public

    JavaScript

  5. Java-Version-Management Java-Version-Management Public

    Java Course Project: Implementation of a Simple Version Control Tool

    Java 2 2

  6. Personalized-Evaluation-System Personalized-Evaluation-System Public

    Forked from Tesseract-R/Personalized-Evaluation-System

    Personalized Assessment System for Students

0