Huang, Tzu-Heng

  Software Engineer           Location: Taipei, Taiwan          E-mail: [email protected]           : LinkedIn.Page


National Cheng-Chi University
Sep. 2016 ~ 2020  Senior Student 
  • Computer Science, GPA 3.97

  • Research field: IoT Ecosystem, Edge Computing, Embedded System, Data Science (ML)


  • Programming Languages: Python, C++ / C, VBA, R, SQL
  • Embedded System: Raspberry Pi (Raspbian), STM32 (Mbed OS), Linked 7688 (OpenWrt) 
  • Others: Git, PCB design (Eagle), LPWAN (Sigfox, NB-IoT), Tensorflow

Invited Talks

  • "The 24th of the Raspberry Pi Meetup". Jan. 2019
    - Attendance 100+

  • "Raspberry Pi Jam". Mar. 2019
    - Attendance 70+

  • "Techbang Magazine PiM25 Project Sharing", Mar. 2019
    - Attendance 60+

  • "LASS Conference International Session", Jul. 2019
    - Attendance 100+

Work Experience

Jul. 2019 ~ Sep. 2019                            Argonne National Laboratory

Research Aide in Array of Things, @Chicago in United States
  • The Array of Things (AoT) is an urban sensing network in Chicago city, measuring factors that impact livability in cities such as climate, air quality, pedestrian, floodwater, and noise.
  • Used machine learning method to calibrate radiative error with current ambient light level.
  • Built pattern recognition algorithm for time series data.
  • Reprogrammed micro-controller firmware and micro-processer in the embedded system.
  • Connected AoT data API and LASS data API to transfer data to each sensor network platform.

Feb. 2018 ~ present                                          Academia Sinica

Research Assistant in Network Research Lab, @Taipei in Taiwan
  • Contributed to Location Aware Sensing System (LASS), the biggest large-scale PM2.5 sensing IoT system with more than 7,000 participating devices over more than 41 countries.
  • Researched edge computing and analyzed multiple time series data.
  • Constructed an optimal deep learning model to forecast air quality.
  • Developed PiM25 IoT device and administered PiM25 community.
  • Tested the first generation of MIT air quality sensor and improved the data quality by a calibration model.

Jul. 2017 ~ present                                National Cheng-Chi University

Research Assistant in the College of Commerce, @Taipei in Taiwan
  • Developed an automotive analysis platform to produce a data report of employees' personality.
  • Increased efficiency of the parsing algorithm by 20%.
  • Designed an employee database according to end user information and predicted employee turnover.


Seq2Seq Model Forecasting Air Quality with Edge Computing

  • Constructed a real time deep learning model to predict PM2.5 data
  • Reduced burden on a cloud server and improved the efficiency and accuracy of the training model

Developed a Low-Cost Devices Calibration Model of PM2.5 Measurements 

  • Provided a correction formula and an open calibrated API
  • Utilized professional weather stations to correct low-cost sensor data
  • The project proposal was accepted with College Student Research Scholarship and approved by MOST

Pattern Recognition for Time Series Data and Calibration Model Improvement (in progress)

  • Applied specific K-means cluster algorithm to recognize time series pattern
  • Improved calibration model to minimize radiative error caused by solar radiation

Adaptive Sample Rate in a Sensor Network for Air Quality Monitoring (in progress)

  • Analyzed time series data and sought the best sampling interval to reduce energy cost

Software Project

Jul. 2019 ~ Sep. 2019                                       System Integration

  • Replicated USB-to-Serial function and uploaded the latest sketch to a self-designed PCB board
  • Reprogrammed a Micro-Controller Firmware into another Micro-Processor chip

Dec. 2018 ~ Apr. 2019                                      PiM25 Community

  • Combined PM2.5 sensor and Raspberry Pi to develop a truly end-to-end IoT ecosystem
  • Built customer data visualization, outlook design, and an efficiently OTA update mechanism
  • The first Taiwan project published on the Magpi (an official Raspberry Pi magazine), and got accepted in
    HKoscon (2019) and COSCUP (2019) to give a talk

Feb. 2018 ~ Mar. 2019              The first generation environmental sensor

  • Tested and deployed more than 70+ environment sensors in Taiwan and reported the error devices 
  • Provided a regression model for pm2.5 sensors to calibrate data and improve data quality

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