Zhou Zihang


Education

BUAA
Beihang University
Bachelor | Computer Science & Technology
2019 - 2023
NUS
National University of Singapore
Master | Computer Engineering
2024 - Now

Skills

Programming Languages: C, Java, Python, JavaScript, HTML, Swift, Verilog.

Frameworks & Tools: React Django MySQL Nginx TypeScript TailWindCSS TensorFlow

Languages: Chinese (Native), English (TOEFL 108)


Projects

Musician and Genre Analysis Research
Meritorious Winner in the MCM/ICM 2021

  • Constructed adjacency lists describing the music influence network topology of musicians, establishing relationships between influencers and followers through weighted directed paths. Computed the music influence value for each musician using DFS recursion
  • Combined graph networks with mathematical modeling to calculate musician similarity using cosine similarity and music feature influence using Pearson correlation coefficient

PetCharm Pet Platform & Campus Takeaway Delivery Platform
Backend Development

  • Built a database system using MySQL
  • Developed backend APIs using Django based on the MVC model, utilizing Nginx and uwsgi reverse proxy
  • Implemented secure login using session and cookie mechanisms, set up email verification and object storage systems

Personal Website
Frontend Development

  • Built personal website using React and TypeScript, enhanced with TailwindCSS

Memo & IoT Monitor
iOS Development

  • Developed iOS apps for diary, book, movie records, and IoT device control using Swift and SwiftUI. Used HTTP to call backend APIs for real-time information and control of IoT devices

PCode Compiler
Java Development

  • Performed lexical analysis, syntax analysis, error handling, and generated Pcode code using finite automata, recursive descent, and other methods

MIPS-CPU
Verilog Development

  • Implemented a 5-stage pipeline CPU based on MIPS instruction set using Verilog

New York City Taxi Fare Analysis & Music Preference Analysis
Peter the Great St.Petersburg Polytechnic University Big Data & Machine Learning Project

  • Employed SVM, XGBoost, deep neural networks, and more for data analysis

Long-term wind prediction in wind farm areas based on machine learning
Graduation Project

  • Implemented wind speed long-term forecasting using a deep neural network based on LSTM