Skip to main content

Nattapon Jaroenchai

Ph.D. Student (Advisor: Dr. Shaowen Wang)
Web Developer, CyberGIS Center

Biography

I am a Ph.D. student in the Geography and GIS department at UIUC. My current research focuses on developing machine learning algorithms to improve the accuracy of remote sensing data to improve our understanding of the Earth's surface and its changing conditions. I am also interested in exploring the potential of GeoAI to enhance decision-making.

Research Interests

  • Spatial Analysis
  • Geoinformation
  • Satellite Image Analysis
  • Geomatics
  • Geo-processing
  • Geographical Analysis
  • Geostatistical Analysis
  • Spatial Statistics
  • Digital Mapping

Education


University of Illinois Urbana-Champaign
Master of Science - Geography and Geographic Information Science  Aug 2017 - Aug 2018
Grade: 3.84
Activities and societies:

  • Participated in iEngage's volunteer event at Weldon Spring State Park
  • Participated in Thai Student Association's events

Chulalongkorn UniversityChulalongkorn University
Bachelor's degree, Computer Engineering 2007 - 2011
Grade: 3.19
Activities and societies:

  • Leader of freshmen of Residence of Chulalongkorn University,
  • Leader of Grandstand Service in CU-TU Traditional Football 66th,
  • Leader of Committee of Residence of Chulalongkorn University

Courses include: Algorithm, Data Structure, Hardware, Network, Software Engineering, Data Mining, Distributed System
Senior Project: Implementation Online System for Collaborative Daisy Audio Book Generation and Sharing

 

Awards and Honors

  • Student of the year 2018, Professional Science Master’s, University of Illinois Urbana-Champaign
  • Leadership Awards 2018, Global Leaders Orange Blue Engagement Program, University of Illinois Urbana-Champaign
  • Student of the year 2020, CyberGIS Center, University of Illinois Urbana-Champaign

Highlighted Publications

  • Xu, Z., Wang, S., Stanislawski, L. V., Jiang, Z., Jaroenchai, N., Sainju, A. M., ... & Su, B. (2021). An attention U-Net model for detection of fine-scale hydrologic streamlines. Environmental Modelling & Software, 140, 104992.

Recent Publications

  • Xu, Z., Wang, S., Stanislawski, L. V., Jiang, Z., Jaroenchai, N., Sainju, A. M., ... & Su, B. (2021). An attention U-Net model for detection of fine-scale hydrologic streamlines. Environmental Modelling & Software, 140, 104992.
  • Stanislawski, L. V., Shavers, E. J., Duffy, A. J., Thiem, P., Jaroenchai, N., Wang, S., ... & Buttenfield, B. P. (2022). Scaling-up deep learning predictions of hydrography from IfSAR data in Alaska. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 48, 449-456.