Projects

• Imputation of Time Series Data via Generative Models and GRU Oct. 2023-Present

  Team leader, Dr. Gong’s group

  • Conduct a thorough literature survey on time series data imputation to identify prevalent limitations and gaps in current methodologies.
  • Develop a GRU-based time-series generative adversarial imputation network algorithm and investigate the mathematical theory underlying the algorithm.
  • Implement the time series imputation algorithm based on different divergence functions using Python.
  • Prepare a manuscript for submission to a peer-reviewed journal.



• Change-Point Detection for Time Series Data Using Scaled Bregman Divergence June 2023 - March 2024

  Team leader, Dr. Gong’s group

  • Developed a Pearson-like Scaled Bregman Divergence Method for Change-point Detection (CPD) of multivariate time series data.
  • Investigated the mathematical foundation of the algorithm and reinforce the algorithm's generality and reliability across a broader range of applications.
  • Reproduced comparative methods in R and Python to benchmark our model against existing techniques. Compare the accuracy in identifying change-points, and performance across diverse datasets and conditions.
  • A paper is under review in a peer-reviewed journal.



• Innovative Web-Based Library Management System Sept. 2023 - Dec. 2023

  Team leader of Course Project

  • Utilized SQL for robust database design and management, ensuring efficient data storage, retrieval, and manipulation; Implement the user interface using HTML, creating an intuitive and responsive web application.
  • Built the core functionality of the system using Python, ensuring seamless integration with the database and frontend components; Apply GitHub for source code management and team collaboration, maintaining an organized and efficient development workflow.
  • Used CircleCI for continuous integration, automating code testing and deployment processes, to enhance code quality and deployment efficiency
  • Employed Docker Hub for containerizing the application, ensuring consistent deployment across different environments.



• Imputation of sc-RNA Sequencing Data via Generative Adversarial Networks Oct. 2022 - May. 2023

  Team leader, Dr. Gong’s group

  • Led the team to develop a novel single cell f-divergence based generative adversarial imputation network (sc-fGAIN) algorithm to impute the missing values in the single cell RNA sequencing data.
  • Implemented the sc-fGAIN algorithm using Python and provide mathematical proofs to confirm its effectiveness and general applicability in imputation tasks.
  • Managed a massive dataset with dimensions 10,164 by 3,918, ensuring efficient data preprocessing and algorithm application.
  • Implemented and compared different state-of-the-art imputation methods as benchmarks using R, Python, and MATLAB to validate the superiority of our approach.
  • Our paper has been published in PLOS ONE in 2023, and receive a Best Oral Presentation Award at 2023 International Conference on Bioinformatics, held in Brisbane, Australia.



• Analytical Text Processing Using Machine Learning Sept. 2022 - Nov. 2022

  Course Project

  • Applied Python libraries Pandas for data manipulation and Scikit-Learn for machine learning model implementation, including using feature sklearn.feature_extraction.text.CountVectorizer for text preprocessing and feature extraction.
  • Processed raw text data using tokenization and lemmatization techniques.
  • Implemented a variety of classification algorithms, including Naive Bayes, SVM, and Random Forest, to compare performance. Optimize models using cross-validation and grid search techniques.



• Statistical Inference and verification of Regulatory Networks Sept. 2020 - May 2021

  Collaborative Research Project, Dr. Gong’s group

  • Applied a weighted dynamic Bayesian network method to reconstruct gene regulatory network from time series microarray data with other team members.
  • Implemented different model checking technique, including SMV and PRISM for the network verification.
  • Wrote a manuscript in collaboration with other team members and a paper was published in 2021

Skills

• Computer Languages: Python, R, MATLAB, SQL, HTML
• Skills:
  • Data analysis for big data;
  • Database skills;
  • Website building skills(basic);
  • Software development(basic)