About me

Hi, This is Zihe Song.
I’m currently pursuing a Ph.D. degree in Computer Science at UTDallas, and working with Prof. Wei Yang. My interested research areas are mobile testing and machine learning.

Education

  • Ph.D. in computer Science, The University of Texas at Dallas, 2020 - Current
  • M.S. in Computer Science, The University of Texas at Dallas, 2018 - Current
  • B.E. in Communication Engineering, University of Electronic Science and Technology of China, 2014 - 2018

Research

  • Department of Computer Science, UTDallas, Oct. 2019 - Current
    Advisor: Wei Yang

Publication

  • An Empirical Analysis of UI-based Flaky Tests, A. Romano, Z. Song, S. Grandhi, W. Yang, W. Wang Accepted by 43nd International Conference on Software Engineering (ICSE’21)

  • An Automated Framework for Gaming Platform to Test Multiple Games, Zihe Song Accepted by 42nd International Conference on Software Engineering ACM Student Research Competition (ICSE’20 SRC)

Projects

  • Mobile Application Testing for Low-power Mode : Feb. 2020 - Current
    • Investigating system impact on applications in power saving mode.
  • Flaky Test in Mobile UI Testing : Feb. 2020 - Current
    • Analyzing flaky tests occurred in mobile application UI testing.
  • Automated Testing Framework for WeChat mini-games : Nov. 2019 - Feb. 2020
    • Designing an automated testing framework for multiple WeChat mini-games.
    • Using evolutionary algorithms and reinforcement learning techniques to build the model.
  • Santander Customer Transaction Prediction : Mar. 2019 - Apr. 2019
    • Created binary classification models based on Light GBM, GNB and SVM algorithms to predict whether the customer will make a transaction with Santander.
    • The dataset contains 200 numerical features and 200,000 instances, the AUC of LGBM model is up to 0.90.
  • Viola-Jones Face Detection : Mar. 2019
    • Wrote code to implement face and blink recognition on real-time photo based on Viola-Jones Algorithm.
    • The detection accuracy is up to 85%.
  • ERC20 Token Transactions Analysis : Nov. 2018 - Dec. 2018
    • Worked with another team member to create discrete distribution models for an ERC20 Token.
    • Analyzed the correlation between number of transactions and price, amount, transaction party, etc.
  • Unix V6 File System : Nov. 2018 - Dec. 2018
    • Worked with another team member to create a Unix V6 file system.
    • Individually wrote code to write, read and delete large files (up to 4 GB).
  • eBay Database System : Apr. 2019 - May. 2019
    • Designed a database system for eBay in 3rd normal form, include procedures and triggers.

Skills

  • Programming languages
    • C, Python, Java, SQL, R
  • Operating Systems
    • Mac(OSX), Windows, Linux(Ubuntu)

Relevant Coursework

Machine Learning, Computer Vision, Statistics in Data Science, Database Design, Algorithms Analysis and Data Structures, Operating Systems, Linear Algebra, Calculus, Data Representation, Combinatorics and Graph Algorithms, Design and Analysis of Computer Algorithms