EDUCATION

• Aug 2021

  Northeastern University

  Master of Engineering: Data Analytics Engineering

• Jun 2018

  Tongji University, China

  Bachelor of Engineering: Computer Science and Technology

SKILLS

• Programming languages C C++ Python R Shell SQL Assembly

• Databases MySQL Oracle MongoDB

• Data Visualization Tableau R Studio Flourish

• Tools TensorFlow PyTorch MATLAB GitHub Jupyter Notebook Google Earth Engine QT Creator Firebase

• Web Development Flask Django HTML5

WORK EXPERIENCE

• Jan 2020 - Aug 2020

  Broad Institute

  Intern, Software Development

  • Applied Jupyter Notebook and shell script to realize automatic quality control of large datasets collected from experiments and batch processing of daily data analysis
  • Modified the acticircadian codes with MATLAB to meet certain analysis needs and data formats
  • Designed and developed a website with python flask, google authentication and firebase, which can be run on cloud sever with certain functions including register, login, data analysis, and downloading

• Nov 2017 - Mar 2018

  Ernst & Young, LLP

  Intern, Performance Improvement Department, Advisory

  • Assisted in decision making by analyzing data with python and performing visualization with Python and R AstraZeneca August 2017–November 2017

• Aug 2017 - Nov 2017

  AstraZeneca

  Intern, IT Department

  • Managed the UI and function design of new platform “PromoMats” aiming to serve as an internal database
  • Produced weekly report on operation performance through monitoring web traffic and user access

ACADEMIC PROJECTS

• Apr 2021

  Master of Science Thesis

  Recurrence plot and CNN based method for human activity recognition

  • Modified data collected by accelerator and gyroscope with NumPy and realized automatic processing
  • Transferred the time series into recurrence plots in the size of 128*128 and classified the plots by different body parts and two sets of activities, running and walking, climbing up and climbing down.
  • Utilized LeNet5 to conduct deep learning. Recorded accuracy, precision, recall, f score and ROC curve
  • Applied visualization to compare the performance and chose the best method to realized recognition

• Dec 2020

  Master of Science Lab Project

  Combining satellite imagery and deep learning to predict civil health conditions

  • Employed Google Earth Engine to automatically download satellite images and divided them into 2500+ segments by applying segmentation methods with python and MATLAB
  • Utilized CNN algorithm to find correlations between satellite imagery and health condition

• Jun 2018

  Undergraduate Thesis

  Emotional Analysis Basing on EEG Signal

  • Designed and operated experiments of collecting EEG signals stimulated by 7 different emotional materials which can be classified into negative and positive ones and processed data with feature extraction
  • Applied CNN and SVM to conduct deep learning with TensorFlow and compared the algorithms
  • Gained progress in accuracy through consultation of 60+ papers and immersion of 540+ hours in laboratory