Experience & Education

My academic and professional journey integrates geospatial data science, artificial intelligence, and environmental informatics. Below is a summary of my education, research, and professional experience.

Education

University of Michigan, Ann Arbor, MI

M.S. in Geospatial Data Science, School for Environment and Sustainability (SEAS)

Sep 2024 – Jun 2026 (Expected) | GPA: 4.0/4.0

Relevant Courses: Principle of GIS, Machine Learning, Advanced Topics in Computer Vision, Advanced Geovisualization, Remote Sensing, Web Design, Master’s Thesis.

Chongqing University of Posts and Telecommunications, Chongqing, China

B.E. in Software Engineering (Joint Program with University at Albany, SUNY)

Sep 2020 – Jun 2024 | GPA: 3.5/4.0 (Rank 15/108)

Selected Courses: Algorithmic Analysis and Data Structure, Programming at Hardware-Software Interface, Principle of Programming Language, Differential Equation.

Professional Experience

China Mobile Co., Ltd., Taizhou Branch, China

Backend Development Intern | Jun 2023 – Oct 2023

  • Developed backend modules for the Taizhou Municipal Approval Bureau information system using Java and Node.js.
  • Optimized framework components and conducted API interface testing to improve stability and efficiency.

Chongqing Tobacco Bureau, Chongqing, China

Data Analysis Intern – Chongqing Tobacco Terminal Layout Project | Aug 2022 – Dec 2022

  • Conducted spatial and statistical analysis for tobacco retail terminal layout optimization.
  • Applied clustering algorithms to identify user distribution patterns across districts.
  • Provided data-driven recommendations for retail network planning and service coverage.

Research Experience

University of Michigan – SEAS, Ann Arbor, MI

Researcher with Prof. Mark Lindquist & PhD Student Xiaohao Yang | Nov 2024 – Present

  • Project 1: Investigating how urban soundscapes and visual imagery affect human affective perception through multimodal machine learning and emotion annotation.
  • Project 2: Identifying and Mapping Urban Blight in Detroit Using Vision–Language Models — proposed scalable blight detection via multi-view imagery and ensemble learning.
  • Project 3: Integrating Multimodal Large Language Models for Urban Spatial Semantic Analysis — comparative study of Zibo and Ann Arbor to bridge spatial and perceptual urban analytics.

University of Michigan – EECS Department, Ann Arbor, MI

Research with PhD Student Zhiwen Wan | Jan 2025 – Apr 2025

  • Extracted battery charge–discharge features and predicted State of Health (SOH) using transformer-based models.
  • Built feature engineering pipelines from voltage, current, and temperature time series data.

Chongqing Intelligent Information Technology & Services Innovation Lab, Chongqing, China

Research Assistant to Prof. Tingting Xu | Mar 2022 – Sep 2023

  • Developed machine learning models for nighttime-light–based socioeconomic parameter prediction (accuracy >95%).
  • Built Grid-GWR-CUDA models for wetland loss and assessed regional spatial heterogeneity.
  • Applied clustering and SHAP-XGBoost to reveal drivers of glacier degradation across China.
  • Implemented CNN–LSTM frameworks to improve urban sprawl simulation performance across multiple resolutions.

Teaching Experience

Chongqing University of Posts and Telecommunications, Chongqing, China

Peer Teaching Assistant / Class Mentor | Sep 2022 – Jun 2024

  • Served as mentor for undergraduate cohorts in Software Engineering with 100% positive student evaluations.
  • Organized midterm and final review sessions and English proficiency (CET-4/6) workshops.
  • Provided one-on-one academic mentoring to improve students’ performance and study strategies.