Hi, I'm Guanming Chen.
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A self-motivated quick starter -- Passionate about technology and enjoy team-working, sharing and being exposed to new learning environment.
About Me
I'm a current master student majored in Computer Science and Engineering in Georgia Tech. My background includes programming, software engineering, data science and web application development. I have 2 developer internships in the tech companies and several projects in full-stack web application development. I'm enthusiastic in the products and eager to explore new technologies and make commitment to the society, not only focus on coding and algorithms, but also pay attention to real beautiful products that can indeed solve problems.
- Knowledge: Object-Oriented Programming, Data Structures and Algorithms, Web Application Development, Software Engineering, Agile Methodology (Scrum)
- Languages: Java, Python, SQL, C, C#, HTML / CSS, JavaScript
- Databases: MySQL, SQLite, SQL Server, MongoDB
- Frameworks: Node.js, Express.js, React.js, Flask, .NET
- Tools & Technologies: AWS, GCP, Azure DevOps, Git, JIRA, Tableau
My Education
Georgia Institute of Technology
Atlanta, USA
Current Attending: Master of Science in Computational Science & Engineering
Duration: August 2021 - May 2023 (Expected)
Current GPA: 4.0/4.0
- Data Structures and Algorithms
- Computational Science and Engineering Algorithms
- Prototyping Interactive Systems
- Intro to Database
- Machine Learning
- Data & Visual Analytics
- AI for Smart City
Relevant Courseworks:
School of Engineering, Civil Aviation University of China
Tianjin, China
Degree: Bachelor of Engineering
Duration: August 2015 - July 2019
Final GPA: 3.63/4.0
- Foundation of Computers
- Introduction to Simulation Engineering
- System Analysis and Intelligent Algorithms
Relevant Courseworks:
University of California in Los Angeles
Los Angeles, USA
Program: 2019 UCLA Summer Program in Samueli School of Engineering
Duration: August 2019 - September 2019
Final GPA: 3.65/4.0
Work Experience
- Migrate current web service architecture to REST for scalability and maintenance ability upgrading, save 60% time when processing the transactions or client request from the platform
- Build 7 RESTful APIs under the 4-layer clean architecture, refine transaction flow following the new API solution
- Update 35 transactions stored in the SQL databases, create 30+ objects and store procedures for data manipulation
- Improve the functionality to process 5 types of transactions, pass the pipeline test and deploy the solution in 3 stages
- Tools: Java, C#., .NET, SQL Server, Postman, Azure DevOps, Visual Studio
- Knowledge: Software Engineering, Web Application Development, REST Api, Agile (Scrum)
- Implemented internal automatic quality-monitoring tool integrated with auto-bot interaction interface using Python
- Committed to the solution design and workflow improvement, the rate of on-time feature delivery was improved by 30% and the total number of bugs per release was decreased by 20%
- Upgraded the application data pipelines including ETL process and analysis approach, enabled the application to automatically analyze quality data from 3 sources in real time, the efficiency was increased by 30%
- Deployed the SQL database and application on servers, responsible for the application maintenance and bug fixing
- Tools: Python, SQL, JavaScript, Linux, Jira
- Knowledge: Software Engineering, Application Development, Data Analyze, Agile (Scrum)
My Projects

A Full-stack Enterprise Online Data Management Platform
- Tools: AWS, React.js, Node.js, HTML / CSS, PySpark, MySQL
- Cleaned and pre-processed over 500,000 meta data with 25+ dimensions using PySpark on AWS cloud platform.
- Established user authentication flow, completed backend connection utilizing Node.js / Express.js frameworks.
- Conducted frontend service through React.js, improved interaction interface via HTML / CSS.

A Online Music Search & Recommendation Engine with Graph-based Visualization
- Tools: GCP, JavaScript, Flask, MongoDB, SQLite
- Performed data processing and dimension reduction of 100,000+ raw data with 15+ dimensions on GCP cloud platform.
- Built MongoDB database, connected backend service and developed restful APIs via Flask web framework
- Programmed frontend development by JavaScript, visualized user interaction utilizing D3.js

A Tree-based Movie Recommendation System using Machine Learning
- Tools: GCP, JavaScript, Flask, MongoDB, SQLite
- Performed data processing and dimension reduction of 100,000+ raw data with 15+ dimensions on GCP cloud platform.
- Built MongoDB database, connected backend service and developed restful APIs via Flask web framework
- Programmed frontend development by JavaScript, visualized user interaction utilizing D3.js
Knowledge and Skills
Knowledge






Languages and Databases










Frameworks




Cloud Platforms and Tools






