(Working Remotely)

Course Enrollment System

I am involved as a full-stack developer in the system that serves 1500+ students.

• Designed and created 5 tables in ​AWS RDS​ ​MySQL ​to allow teachers add/delete courses, students enroll/drop courses

• Programmed enrollment website with ​JavaScript​ via ​React​ using ​React Router​, ​React Hook​, and

Material UI​. Deployed on ​AWS S3 ​with static web hosting

• Built a back-end service using ​Java​-based ​Spring Boot​. Published docker image with ​Google jib​ to ​AWS Elastic Container Registry (ECR)

• Created and deployed dev & prod environment with 5 nodes each on ​AWS​ ​Elastic Kubernetes Service

(EKS) ​with ​Elastic Load Balancer ​integrated

• Introduced ​GitHub Action​ as ​Continuous Integration​ to reduce deployment time by 83%

• Configured and connected MySQL with ​Hibernate​. Implemented all back-end APIs with ​RESTful convention. Introduced​ JWT token​ using ​Spring Security​ and stored it as cookies in front-end

Online Comment Stream Processor

• Set u​p a data ingestion layer with internal live comment streaming API with ​Python

• Implemented a real-time comment processor with ​Apache ​Spark​ ​for live-streaming comments

• Introduced statistic ​chart for top 10 comments using ​Ajax​ long polling with 3s interval

• Deployed and configured ​Google Cloud Platform VM instance​ to support external viewing

Real Time Sentiment Analysis

• Built event queuing layer with ​​Kafka​​ to process input dataflow

• Implemented sentiment monitor with​ ​Apache Spark​​ capable of handling up to 60 comments per second

• Visualized real-time positive vs. negative sentiments trends using ​Python

• Created analytic dashboard using ​React ​to showcase different teachers’ popularity among online audience

• Helped advertisement team to analyze audience’s preference, which increased course income by 10% and new user registration by 30%

Low Power Environmental Sensing System

(Researcher under Prof. Bob Iannucci, CMU)

• Commissioned by United State Geological Survey (USGS) with million dollars of funding

• Developed a low-power wireless sensing system for collecting stream height data of Pepperwood Preserve, Sonoma County, California, achieved 10X battery life time extension with advance low power technology

• Enabled lower power communication between sensing systems and gateway via LoRa

• Reduced the cost of 5+ rangers/year for monitoring the stream height manually

• Led a 4-engineer firmware team for this complicated system with 14 components

• Implemented firmware for 5 sensors with hardware interfaces​ UART​,​ I2C​ and ​SPI ​using​ C

• Used ​JTAG​, ​Logic Analyzer​ and​ Oscilloscope​ extensively

• Used ​Python​ to orchestrate transmitter and receiver for LoRa signal strength data collection

Researcher under Prof. Vijay Sivaraman, UNSW

• Managed a team of 4 engineering students to build a system that estimates the bus queue length, waiting time, and recommend the bus stop with shortest waiting time to users via mobile application

• Utilized Python and mySQL API to implement user and bus data acquisition, resulting in a backend flask server bridging between web/mobile application and databases for 5 real-time parameters

• Innovated the method of QR code scanning along the bus queue to track the queue length

• Enhanced over 10 existing BMW automatic car diagnosing system

• Collaborated with 6 cross-functional teammates to refine over 20 Electronic Control Units circuit design

• Communicated between over 6 customers and technical teams to help customers understand the technical transformation that their cars are going through in a daily basis