f26401004
Chun-Hao Huang
Mount Vernon, United States

I received a bachelor degree in Computer Science and Information Engineering at National Cheng Kung University, focusing on software engineering, networking.

CodersRank Score

What is this?

This represents your current experience. It calculates by analyzing your connected repositories. By measuring your skills by your code, we are creating the ranking, so you can know how good are you comparing to another developers and what you have to improve to be better

Information on how to increase score and ranking details you can find in this blog post.

804.8
CodersRank Rank
Top 1%
Top 100
C++
C++
Developer
United States
Top 50
SASS
SASS
Developer
United States
Top 50
Vue
Vue
Developer
United States
Highest experience points: 0 points,

0 activities in the last year

List your work history, including any contracts or internships
National Chiao Tung University Full-time
Sep 2020 - Jan 2021 (4 months)
Hsinchu City, Taiwan
Network Research Assistant
Project – Mobile/Multi-access Edge Computing (MEC) Middlebox
• Constructed multi-cluster orchestration platform in MEC middlebox integrated with Kubernetes.
• Utilized OpenAirInterface, radio access network, LISP tunneling, multi-cluster orchestration system.
• Supported 23 DNS providers for end-users to customize domain name of services.
Kubernetes docker docker compose
CityChaser Studio Self-employed
Nov 2019 - Sep 2021 (1 year 10 months)
Taipei City, Taiwan
Co-Founder & Full-stack Engineer
Product – Kyronus
Developed cross-platform mobile simulation game championing Taiwan culture of historical site.
Key tech: mobile application framework, serverless computing, cloud, software engineering, DevOps.
• Proposed and integrated Apache Cordova into project to build one-codebase hybrid (Android & iOS) mobile app.
• Shortened app development cycle by proposing and integrating Apache Cordova into project to build an one-codebase hybrid mobile app (Android & iOS).
• Avoided generating excessive load to API server by implementing truncated exponential backoff on front-end API requesting in Axios interceptors.
• Improved frame rate up to 200% in map-related operation (scaling, rotating, relocating, ...etc) by building Cordova native plugin with Mapbox SDK.
• Introduced DevOps pipelines using GitLab CI/CD and Docker for Android automatic deployment in semantic versioning and thus successfully shortened development cycle time by up to 50%.
• Reduced Docker image's size by up to 300% with Multi-Stage Builds tech to accelerate the build and deployment processes.
• Led 7-person team and coordinated all Scrum Ceremonies including Sprint Planning, Daily Stand-ups, Sprint retrospectives, Sprint Demos, Story Grooming, and Release Planning resulting in on-time delivery rate of 95%.
• Built multiple kernel components of game mechanisms: collect resource system, mining system, offline countdown timer, and so on.
• Constructed several back-end APIs for collect resource system, email system using Express.js, DynamoDB, AWS Lambda, and AWS Gateway.

see more
Android serverless devops cloud Docker dynamodb aws lambda ci/cd
FarEasTone Telecom Full-time
Jul 2019 - Aug 2019 (1 month)
New Taipei City, Taiwan
Web Development Internship
Project – KPI dashboard
Constructed web-based dashboard to produce detailed monthly KPI reports automatically.
Key tech: web UI library, database, Object-relational mapping, PSD to HTML, secure transport protocol.
• Used jQuery to built mobile UI adopting Responsive Web Design to work smoothly on both mobile and desktop devices.
• Build real-time dashboard chart with Apache ECharts and implemented periodically API requesting using JavaScript closure.
• Enabled HR to import KPI data from Microsoft Excel spreadsheets into Django model.
• Automatically generated monthly KPI reports using shell script and Linux crontab and thus decreased HR daily workload by 13%.
• Directed 3-person team and completed the project 2 weeks in advance with an additional 13-page documentation slashing job handover.
• Proposed AAA (Authentication, Authorization, and Accounting) secure transport protocol using Kerberos and Microsoft Active Directory.

Project – Fraud call detection
Trained a ML model for fraud call detection.
Key tech: classifier, feature engineering, data pre-processing.
• Utilized Recursive Feature Elimination (RFE) and bagged decision trees to reduce number of features from 52 to 20 and successfully reduced training time.
• Applied weighted average ensemble (LightGBM, GradientBoosting, XGBoost, CatBoost, and RandomForest) to final prediction and thus improved precision rate by up to 10%.
• Built a multi-classifier with 94% precision to detect fraud call with FarEasTone Telecom's anonymous data.
Django HTML jquery JavaScript

Jobs for you

Show all jobs
Feedback