Yining Wang

Contact me via: freya.yini@gmail.com

EDUCATION

  • Northeastern University

    Candidate for Master of Engineering: Data Analytics Engineering

  • 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

  • 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
  • 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
  • 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

  • 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
  • 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
  • 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