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Gengchen Mai

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Assistant Professor, Department of Geography

My name is Gengchen Mai (买庚辰). I am a tenure-track assistant professor at the Department of Geography, University of Georgia, as a member of the UGA Environmental Artificial Intelligence Faculty Cluster

I got my Ph.D. in Cartography and Geographic Information Science from Department of GeographyUniversity of California, Santa Barbara. I was a graduate student research at both Space and Time for Knowledge Organization (STKO) Lab and UCSB Spatial Center. I am interested in Machine Learning/Deep Learning, Geographical Information Science (GIScience), Geographic Question Answering, NLP, Geographic Information Retrieval, Knowledge Graph, and Semantic Web. Right now, my research is highly focused on Geographic Question Answering and Spatially-Explicit Machine Learninig models. I have completed five AI/ML research based internships at Esri Inc.SayMosaic Inc.Apple Map, and Google X.

Before I become a MA/Ph.D. Student at UCSB, I got my B.S. Degree in Geographic Information System from Department of Geographical Information Science, School of Resource and Environmental SciencesWuhan University. During my undergraduate study, my research topic, especially undergraduate thesis, is focused on Land Use/Cover Change (LUCC), spatial analysis and spatial statistics.

For students interested in joining Dr. Mai's team, please send your resume to gengchen.mai25@uga.edu.

Education:

Ph.D. in Cartography and Geographic Information Science from Department of Geography, University of California, Santa Barbara

B.S. Degree in Geographic Information System from Department of Geographical Information Science, School of Resource and Environmental Sciences, Wuhan University

Research Interests:
  • Spatially Explicit Machine Learning
  • Geographic Question Answering
  • Computational Sustainability
  • Knowledge Graph/Representation
  • Ontology Engineering
  • Nature Language Processing
  • Geographic Information Retrieval
  • Machine Learning/Deep Learning
  • GIScience
  • Spatial Data Mining
  • Social Sensing and Urban Analytics
  • Spatial Statistic/Analysis

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