Research Theme

• Comprehensive dataset & urban development patterns
  Developing a comprehensive dataset to analyze urban development patterns.
• Rural and urban
  Exploring the dynamic relationship between rural and urban concepts in contemporary China.

Professional Experience

• Back-end Data Analyst
  • June 2022 – August 2023
    • NielsenIQ.
  • Conducted an in-depth sales data analysis of over 500,000 transactions across all LAN Uniliever stores. Utilized SQL for data querying and Python for statistical analysis. Used analytical tools like Tableau and Excel to visualize sales data and furnishing an explicit comprehension of brand performance and market trends
  • Performed comparative assessments of 20 key brands, targeting essential KPIs such as market share, growth rate, and customer satisfaction scores. Authored multiple bussiness standard 30-page report offering strategic recommendations for maximizing sales and improving brand penetration in highly competitive markets.
  • Developed and presented 10 business decks, each consisting of 15-20 slides, which highlighted critical findings from the evaluations. Emphasized clarity and impact in data visualization by incorporating a mix of charts, graphs, and infographics created using PowerPoint and Adobe Illustrator.

Research Experience

• Analysis of COVID-19 Recovery in U.S. Parks through Multitudinal Data Integration
  • November 2023 – Present
    • Investigator, Nature.AI Lab / MA Thesis, University of Chicago.
  • Collected over 3,000,000 comments from Google Reviews on parks and 70 GB of visual data from Google Street View images focusing on park entrances by using URL Engineering, then cleaned and coded them.
  • Utilized Dynamic Bertopic Modeling to categorize the comments from Google Review and PSPNet to evaluate the cleanness, greenness, and other features, then joined them together with the number of visiting/visitors from Dewey Dataset to study the dynamics of societal recovery from the pandemic.
  • Developed deep learning models to establish correlations between the socioeconomic statuses of neighborhoods and their recovery timelines from COVID-19; currently continuing to fine-tune these models for enhanced predictive accuracy

• Research on Dynamics of Transfer Payment in Chica
  • May 2024 – Present
    • Research Assistant, Rutgers University.
  • Assisted Professorr Xian Huang collect over 20,000 government documents related to social insurance from both central and local Chinese authorities, including laws, local work documents, and local guiding documents.
  • Developed specialized dictionaries tailored to the nuances of social insurance and transfer payment documents, and employed Word Embeddings techniques to perform dynamic topic modeling and word clustering, facilitating in-depth thematic analysis of the documents.
  • Performed a network analysis on documents detailing transfer payment practices to identify patterns of financial support between regions since 2013, demonstrating an increased popularity of interregional transfer payments post-2013 and a decline in intra-regional payments.

• Exploration of Urban Environment as an Association to Human Cognition and Well Being
  • June 2024 – Present
    • Research Assistant, Oishi Lab.
  • Independently scraped over 100 GB of text data from Google Business Reviews across 17 different building types from 104 cities, by using URL engineering methods.
  • Implemented large-scale topic modeling to dissect and analyze how different building types influence emotional responses, including happiness and psychological richness, and fine-tuned analytical models to enhance context relevance and accuracy in interpreting complex emotional data derived from unstructured text.
  • Participated in the research design of measuring the association’s perceived community center and coverage and socioeconomic status of each community.

• Research on the Role of People’s Daily in Reflecting the Development of Neoliberalism
  • May 2022 – December 2023
    • Undergraduate Summer Research Workshop, New York University.
  • Leveraged the People’s Daily, the Chinese Communist Party’s official newspaper, as a primary source to explore the evolution of neoliberal ideology in China’s unique social complex from the start of the Opening-up Policy from 1980 to 2020.
  • Conducted a qualitative study under the guidance of Professor Rebecca Karl, manually coding vocabulary reflecting aspects of neoliberal ideology in the People’s Daily newspaper, and selected key articles to illustrate changes in the representation of this ideology.
  • Collected around 10 GB of articles, highlighting the nuanced development of neoliberal thought within the party’s policy framework, performed keyword identification, frequency analysis, semantic relationship analysis, word2vec models and causal inference under the guidance of Professor James Evans and Dr. Linjia Shi later in University of Chicago.