About Me

Name: GONG ZEQUN
Email: zequn.gong@u.nus.edu
Tel: (+65) 82438479
Github: gongzq5

Education

National University of Singapore Singapore, 2020 – present

Master of Data Science and Machine Learning

Sun Yat-sen University Guangzhou, China 2016 – 2020

Bachelor Degree, Software Engineering.

Internship

Huawei Technologies Co., Ltd. Dongguan, China 2019.7 – 2019.9

Software Engineer Intern, Fenix Development Department

Brief introduction: Maintaining job for a virtual network platform.

  • Rewrite building system by CMake.
  • Adjust the code structure and API.

Projects experience

Comprehensive Course Project on Machine Learning

Use multiple tranditional machine learning methods to analyze and do the predictions on Adult dataset.

  • Analysis with Pandas, Matplotlib, as well as PCA etc.
  • Supervised Learning: Logistic Regression / SVM / Nerual Network / Decision Tree / Random Forest etc.
  • Unsupervised Learning: K-means

Campus Social Platform Link

A platform that provides an employment mechanism. Can make friends, post information, and survey questionnaires etc.

  • Work with 6 teammates.
  • Use professional software engineering tools to manage the team project progress, and finish the project with about 3 months.
  • Provide detailed project documents. Using Vue, Node.js(KOA2 framework) and MySQL.

LFTP File Transfer Application Link

Applied User Datagram Protocol (UDP) conducted 100% reliable data transmission, flow regulation and congestion control with multithreadings and Java API.

Course Card: Electronic School Timetable App for SYSU Link

Use Android (okHttp+RxJava) to develop a course timetable app for SYSU. Can automatically crawl the timetable from the school website.

NUS Tour App Link

Quickly learn and develop a backend of a NUS Tour App using Springboot+Mybatis in a few days. Design and provide RestFul API. Deployed on AWS.

Competition Experiences

Shopee Code League 2021 03/2021

3 Competitions. One Data Analytics competition about finding the same user based on multi-channel informations. One Data Scientist competition about extracting the needed part of a natural addresses. And finally a programming contest.

  • Multi-channel Contacts(ranked 36/964 in Kaggle).
  • Address Element Extraction(ranked 13/1034 in Kaggle).
  • Final Awards: Top 30.

Kaggle LANL Earthquake Prediction Contest

Conducted a predictive analysis of earthquake time based on crustal fluctuation data. Using CNN + LSTM/RNN to extract features and
predict the result.

Sun Yat-sen University Collegiate Programming Contest (ACM) 12/2017

Programming contest using various data structures and algorithms. Get third Prize (Ranked top 30 among over about 150 teams).

Supplementary Information