CV

Education

• PhD in Geography & the Environment, The University of Texas at Austin, 2025 – Present
• Master of Environmental Planning, University of California, Berkeley, 2021 – 2023
  • Certificate in Geographic Information Science & Technology (GIST)
  • Certificate of Teaching and Learning in Higher Education
• B.S. in Environmental Management and Technology, Hong Kong University of Science and Technology, 2021

Work Experience

• Graduate Research Assistant (2025 – Present)
  • GISense Lab, UT Austin
  • Research on GeoAI, multimodal place perception, and human–environment interactions
  • Supervisor: Prof. Yuhao Kang
• GIS Analyst (2024 – 2025)
  • EarthDefine, LLC
  • Developed deep learning pipelines for sub-meter urban land cover classification using NAIP imagery
  • Contributed to the National Urban Tree Cover Map with the Arbor Day Foundation
• Lecturer (Fall 2023)
  • UC Berkeley
  • Instructor of record for GEOG/LDARCH C188: Geographic Information Science
  • Taught Berkeley’s largest GIS course with 200+ students
• Graduate Student Instructor (2022 – 2023)
  • UC Berkeley
  • Taught labs for Applied Remote Sensing (ESPM/LDARCH C289) and GIScience (GEOG/LDARCH C188)
• Research Assistant (2022 – 2024)
  • UC Berkeley & Partner Projects
  • Projects on wildfire burn severity, post-wildfire flood risk, urban forestry microclimate modeling, and wetland conservation

Research Experience

• GeoAI & Remote Sensing Research
  • Deep learning for land cover mapping, multimodal embeddings, and spatial perception modeling
  • Working with high-resolution satellite imagery, LiDAR, and street view data
• Urban Microclimate & Ecosystem Services
  • Using LiDAR, simulations, and tree classification to study cooling, shading, and environmental justice
  • Manuscript under review at Landscape and Urban Planning
• Climate Resilience Modeling
  • Spatial modeling of wildfire, flooding, and ecosystem services to support planning and adaptation

Skills

• Programming Languages
  • Python
  • R
  • SQL
• Machine Learning & AI
  • PyTorch
  • TensorFlow
  • scikit-learn
  • segmentation_models_pytorch
• Geospatial Analysis
  • ArcGIS Pro
  • QGIS
  • Google Earth Engine
  • GDAL, rasterio, geopandas
• Remote Sensing
  • LiDAR processing
  • Object-based image analysis
  • Classification workflows
• Data Visualization
  • matplotlib, seaborn
  • ggplot2
  • Leaflet, ipyleaflet
• Languages
  • English (Fluent)
  • Mandarin Chinese (Native)

Recent Achievements

• Starting PhD at UT Austin in Fall 2025, joining the GISense Lab
• Mentored NASA DEVELOP Fall 2024 project on urban canopy cover & heat in San Jose
• Presented at MIT Senseable City Lab and Stanford Natural Capital Symposium (2024)
• Manuscript on urban forests, LiDAR classification, and microclimate simulation under review

Publications

Mapping of coastal surface chlorophyll-a concentration by multispectral reflectance measurement from unmanned aerial vehicles

Chan, S. N., Fan, Y. W., & **Yao, X. H.**

From Local to Micro: Exploratory Data Analysis on Urban Forests and Microclimates in Portland, Oregon, USA

**Yao, X.**, & Kim, M.

Light pollution impact assessment in Hong Kong: Multi-dimensional measurement and spatial numerical modelling on integrated light sources in the neighbourhood level

Tong, J. C. K., **Yao, X. H.**, Lau, E. S. L., Cheung, W. K. S., Ho, K. K. S., Ng, V. Y. Y., & Lau, A. P. S.

A Lidar-based Method for 3D Urban Forest Evaluation and Microclimate Assessment, a Case Study in Portland, Oregon, USA

**Yao, X.**, & Kim, M.

Community-scale microclimate simulation using Airborne Laser Scanning and object-based urban tree classification

**Yao, X.**, Kim, M., Dronova, I., McBride, J. R., Kondolf, G. M., & Radke, J. D.

Talks

Teaching

Teaching experience 1

Teaching experience 2