Ruiqi Wang Email and Phone Number

Acquired by Culture Amp.1. Lead the backend team building a fast, robust and scalable backend Web Service in Ruby/Rails 2. Lead the data engineering team building the serverless data infrastructure forcontinuous feedback candidate recommendation engine using AWS Lambda, SQS, Redshift, ApacheTinkerpop, etc.

Doing some cool stuff here

Continuous Human Action Recognition based on Kinect1. Up to 92\% recognition accuracy rate using supervised learning method: applied covariance of 3D joint relative locations as the descriptor and Support Vector Machine as the classifier. (MSR Action3D and HDM05 dataset)2. Efficiency and Accuracy Trade-Off: used KPCA to trim the descriptors, which improved the algorithm efficiency by 12 times and got an up-to 83\% accuracy rate3. Designed and implemented the algorithm bsed on open-source SVM library in Python, developed a Kinect based action imitation game (in C\#) using the recognition algorithm as the coreGreen Office Environment Monitoring and Quality Analysis1. Modified BACnet Stack source code to make it compatible with different sensors and equipments in CESL lab2. Built an indoor environment monitoring system using BACnet Stack, python bottle framework and MySQL for collecting data from sensors monitoring various substances (CO2, CO, PM2.5) and equipments control (Light, AC, Curtain, etc)3. Analyzed the data collected daily to provide warnings and suggestions to improve the indoor environment

Adaptive Battery Modeling and State Estimation System1.Utilized adaptive battery model to get the accurate SoC (State of Charge) of real electrical vehicle's battery based on its voltage, current and temperature changes in every fifteen seconds2.Used NI LabView for system simulation to find system design faults and risks3.Implemented the battery monitoring system on SBC TS-7800 in C, which was robust and ready to be applied on Plug-In Hybrid Electrical Vehicles4.Designed a GUI on a programmable 4D-Systems LCD screen for system control and display