Lab Director
Dr. Gengchen Mai is currently a Tenure-Track Assistant Professor at the Department of Geography and the Environment, University of Texas at Austin, and an adjunct professor at UGA Geography. He got his Ph.D. in Geographic Information Science from the Department of Geography, UC Santa Barbara and B.S. in GIS from the Department of Geographical Information Science, School of Resource and Environmental Sciences, Wuhan University. Before becoming a faculty, he was a Postdoctoral scholar at Stanford Artificial Intelligence Laboratory, Department of Computer Science, Stanford University. Before joining UT, he was an Assistant Professor at the Department of Geography, University of Georgia. Dr. Mai’s research is Spatially Explicit Artificial Intelligence, Geo-Foundation Models, Geographic Knowledge Graphs, etc. As one of the leading researchers in Geospatial AI, Dr. Mai has published not only in top-tier AI/GIScience/Remote Sensing journals such as ISPRS Journal of Photogrammetry and Remote Sensing, International Journal of Geographical Information Science, GeoInformatica, AI Magazine, etc. but also top ML/AI/GIScience conference proceedings such as NeurIPS, ICML, ICLR, ACM SIGIR, ACM SIGSPATIAL, ACM K-CAP, etc. Dr. Mai has received many prestigious awards including AAG 2021 Dissertation Research Grants, AAG 2022 William L. Garrison Award for Best Dissertation in Computational Geography, AAG 2023 J. Warren Nystrom Dissertation Award, Top 10 WGDC 2022 Global Young Scientist Award, the Jack and Laura Dangermond Graduate Fellowship. According to the historical records of AAG award recipients, he is now the sole recipient in history to have received three AAG doctoral dissertation awards since 2000. He has completed five AI/ML research based internships at Esri Inc., SayMosaic Inc., Apple Map, and Google [X]. Dr. Mai was an AI advisor for Google [X] in 2020.
Industry Consultant
Dr. Ni Lao is a staff research scientist at Google. He holds a Ph.D. degree in Computer Science from the Language Technologies Institute at Carnegie Mellon University. He is an expert in Machine Learning (ML), Knowledge Graph (KG), Natural Language Processing (NLP), and large language models (LLMs). He was the Chief scientist and co-founder of Mosaix.ai, a voice search AI startup. At Google he works on LLM pretraining, alignment and agent technologies for the next generation of search. Currently, Dr. Lao is a UT-affiliated researcher and the industry consultant of SEAI Lab.
Dr. Hongxu Ma is a staff AI Research Engineer at Google. He holds a Ph.D. degree in Earth System Science and Computational Engineering from UC Berkeley. His research interests include LLM agents, complex systems, causal ML, and predictive modeling. At Google, he works on LLM applications and agent products, such as Google Data Science Agent, which is an automated LLM agent to help with all data science tasks. Currently, Dr. Ma is a UT-affiliated researcher and the industry consultant of SEAI Lab.
Dr. Jinmeng Rao is an AI Research Engineer at Google DeepMind. He holds a Ph.D. degree in Geographic Information Systems and a M.S. degree in Computer Sciences from UW-Madison. His research areas include Generative AI, Privacy-Preserving AI, and Geospatial AI. He was a Research Scientist at Google [X]. At Google DeepMind he works on generative AI research. Currently, Dr. Rao is a UT-affiliated researcher and the industry consultant of SEAI Lab.
Current Members
Qian Cao is a Ph.D. student at the Department of Geography, University of Georgia co-advised by Prof. Angela Yao and Prof. Gengchen Mai. She received an M.S. and B.S. in Urban Planning from Nanjing University. Before coming to UGA, she spent years working as an urban planner in China, focusing on regional planning and research. Her recent research interest mainly lies in the intersection of urban geography and GIScience, especially heterogeneous network representation learning, and GeoAI fairness.
Nemin Wu is a Ph.D. student in Geography and a Master’s student in Artificial Intelligence at the University of Georgia. She is currently under the supervision of Prof. Lan Mu and working closely with Prof. Gengchen Mai. She earned her Bachelor’s degree from Wuhan University. Her research is focused on spatial heterogeneity, spatial representation learning, and GIS for health and environment. Nemin has been recognized with several awards, including 1st place in the 2024 AAG GISS Graduate Student Honors Paper Award, 1st place in the 2024 Graduate Student Lightning Talk Competition on GIS Day at UGA, and 1st place for her presentation at the 10th Annual Health Services Research Day at Emory University.
Zeping Liu is a first-year PhD student in the Department of Geography and the Environment at the University of Texas at Austin, under the supervision of Prof. Gengchen Mai. He earned his M.S. from Beijing Normal University and his B.S. from East China Normal University. His research focuses on Geospatial AI and Intelligent Earth Observation. He was awarded Zhou Tingru Geography Youth Award, China National Scholarship for Graduate Students, Outstanding Graduate of Beijing, etc.
Jielu Zhang is a fourth-year PhD student in the Department of Geography at the University of Georgia and a first-year Master’s student in the School of Computing at the same university. She is currently under the supervision of Prof. Lan Mu and working closely with Prof. Gengchen Mai. Her research primarily focuses on GeoXAI, GeoHealth, and foundational models in remote sensing. She was awarded the Campus Sustainability Award in 2023.
Yanlin Qi is a fourth-year PhD candidate at the Institute of Transportation Studies, University of California, Davis. She is also pursuing an M.S. in Statistics at UC Davis. She earned her M.S. from Peking University and her B.S. from Wuhan University. Her research interests include transportation safety, geospatial AI, and geographic knowledge graphs.
Zhangyu Wang is a fourth-year Ph.D. student in the Department of Geography at the University of California, Santa Barbara. He holds a bachelor’s degree in Architecture from Tsinghua University, a master’s degree in Computer Science from the University of Massachusetts Amherst, and a master’s degree in Mathematical Statistics from the University of California, Santa Barbara. He collaborates closely with the SEAI Lab and has published first-author papers at top AI and GIS conferences. His research focuses on establishing the theoretical foundation for GeoAI algorithms and expanding GeoAI research to a larger scale (Geo Foundation models), broader modalities (points, polylines, polygons), and more general intelligence (generative models).
Dr. Lishen Mao is currently a research scientist at the Institute of Geology and
Environmental Monitoring at Beijing, China. He will be joining the SEAI lab as a
Visiting Scholar from Jan 1st, 2025. Lishen has a broad background in wetland ecology, salt marsh Biogeochemistry and carbon cycle modeling. He received his Ph.D. in Geography from the University of Georgia where he studied the response and feedback of salt marshes to natural disturbance and environmental change. His work primarily involves understanding and modeling carbon cycles, and vegetation dynamics in Earth’s coastal ecosystems. He used field measurements, satellite data, process-based Earth system models, as well as various statistical methods, including machine learning in his research. He received his M.S. from Eastern Michigan University where he studied the interaction between spatial and temporal variations of environmental gradients and grassland primary productivity. Lishen attended Wuhan University where he earned B.S. degrees in Software Engineering.
Shaowen Li is a fifth-year Landscape Architecture student at SUNY-ESF, holding dual bachelor’s degrees from Henan Agricultural University and SUNY-ESF. He is an honor member of ALSA and Sigma Lambda Alpha. Shaowen has participated in plant gene research, published related articles, and won awards in competitions like CHALSA, the Garden Cup, and Milan Design Week. He is currently a Research Assistant contributing to the I-81 urban planning project in Syracuse, New York.
Joshua Ni is a 12th grade student at Basis Independent Fremont. He has been working on using AI/ML/LLM for Wildfire Prediction with a scientist from Lawrence Berkeley National Lab since 2022 and participated in 2 summer internships, which resulted in 3 first author submissions to AGU24 and NeurIPS24. He has volunteered to work with SEAI Lab and its members, contributing to two papers. In his spare time, he has implemented an AlphaGo-like AI game player based on reinforcement learning.
