Experience

  1. Graduate Research Assistant

    University of North Carolina at Chapel Hill
    • [Machine Learning | GUI] Created an open-source Python-based computer vision toolkit (UrbanTrace) to detect urban changes at the building level using high-resolution aerial imagery, incorporating deep learning models (YOLO, Siamese Networks), and integrated the tool into a QGIS plugin with PyQt.
    • [Computer Vision] Processed and analyzed large-scale geospatial datasets (6.5M buildings across 35,000+ square miles) using Python, PyTorch, OpenCV, and GIS frameworks.
    • [LLM] Use Large Language Models via LangChain—including GPT-4, Claude 3, Qwen2, and LLaMA 3—to conduct sentiment analysis on 10,000+ Twitter/X posts, evaluating public perception of New York City’s congestion pricing plan.
    • [Causal Inference] Use logistic regression, spatial econometric analysis, and an explainable machine learning model (XGBoost+SHAP) to examine urban development trends and demographic shifts with various Python packages
    • [Supervision] Provided data analysis (Python and R), machine learning, and GIS support to lab researchers and supervised undergraduate and master’s students.
  2. Transportation Planner

    HDR, Inc.

    AI and Data Related:

    • [ETL] Developed a Python + VBA pipeline to warehouse, analyze, and visualize transportation data from various sources (MySQL, CSV, OData) across the NY/NJ region
    • [MySQL] Designed and developed a Windows tablet survey application using Python and PyQt, enabling surveyors to collect 5000+ questionnaires with automated daily uploads to a central MySQL server.
    • [Data Visualization] Built interactive live data dashboards in Tableau, integrating MySQL databases to visualize transportation analysis results.
    • [Workflow Automation] Automated data analysis and visualization by developing VBA macros in Excel and Adobe Illustrator.
    • [Data Collection] Supervised 10+ third-party traffic data collectors in the field and ensured data quality Planning and Design Related:
    • Develop traffic models to assess the environmental impacts of various types of developments.
    • Supervised 10+ third-party traffic data collectors in the field for data collection.

Education

  1. PhD in City Planning

    University of North Carolina at Chapel Hill
    Thesis: “Explore Urban Regeneration Pattern, Drivers, and Social Impacts in the Southeastern United States Through AI-Powered Analysis” . Supervised by Prof Yan Song. Presented papers at planning journals and AI conferences.
  2. MS Computer Science (Ongoing)

    Georgia Institute of Technology
  3. Master of City and Regional Planning

    Univeristy of North Carolina at Chapel Hill
  4. BEng in Urban Planning

    School of Architecture, Southeast University
Skills & Hobbies
Programming Languages
Python
R
SAS
SQL
VBA
Platforms & Frameworks
Slurm
Google Colab
Jupyter
Langchain
VSCode
ArcGIS
QGIS
Tableau
Libraries
PyTorch
Scikit-Learn
OpenCV
Pandas
GeoPandas
XGBoost
SHAP
Matplotlib
ggplot2
Methods
Linear/Logistic Regression
Spatial Autoregressive Models
Tree-based Models
CNN (ResNet, YOLO, etc.)
LLM
Hobbies
History
Dogs
Photography
Awards
Carolina Data Challenge 2022 First Place
University of North Carolina at Chapel Hill ∙ October 2022
Social Science Track: “Flood? Let’s Help! San Francisco Flood Health Vulnerability Analysis” Analyzed the influencers of flooding risk in San Francisico with KNN, Random Forest and SHAP.
Transportation Leadership Fellows
University of North Carolina at Chapel Hil ∙ January 2020
China National Undergraduate School Social Study Competition
China Ministry of Education ∙ September 2011
Languages
100%
English
100%
Chinese
25%
Cantonese