May Yuan
(Ashbel Smith professor of GIS, University of Texas at Dallas)

Date：Friday, November 14 - 10:00AM~13:00PM  (Taiwan Time, GMT+8)
Topic：Spatial Thinking in Machine Learning and Artificial Intelligence
Registration：Https://utd.link/DAC20251113/(歡迎事先報名、註冊，填寫NCHU-姓名)
Webinar：(待通知)


Abstract：
Spatial Thinking in Machine Learning and Artificial Intelligence
Tversky (2019), in her seminar book, Mind in Motion, claimed that all thought begins as spatial thought.  We move in space, interact with space, use space to think, and think about space. Our actions (live, move, and act) in a physical world are fundamental to our thoughts, whether concrete or abstract. Her claim is backed up by neuroscience findings of spatial codes for human thinking. Spatial thinking is at the core of Geospatial Science (a.k.a., Geographic Information Science – GIScience, Spatial Computing, and Spatial Data Science), to develop conceptual and computational frameworks for understanding geographic worlds.  From human thinking to machine learning, spatial concepts are also instrumental to the progression of machine learning and artificial intelligence and continue to subserve advances in data and algorithms. This talk will discuss what and how spatial thinking is ingrained into popular machine learning algorithms and manifests in the transition from perception AI, generative AI, and Agentic AI to Physical AI. Finally, the talk posits that spatial thinking is essential to the realization of Artificial General Intelligence. 

Description：
May Yuan received all her degrees in Geography: B.S. 1987 from National Taiwan University and M.S. 1992 and Ph.D. 1994 from the State University of New York at Buffalo.
She is Ashbel Smith Professor of Geospatial Information Sciences (GIS) in the School of Economic, Political, and Policy Sciences at the University of Texas at Dallas (UT-Dallas). She is an elected fellow of the American Association for the Advancement of Science (AAAS), the American Association of Geographers (AAG), and the University Consortium of Geographic Information Science (UCGIS).
She serves as the Editor-in-Chief of the International Journal of Geographical Information Science. From July 2022 to July 2025, she was on an assignment to the National Science Foundation (NSF) as a program director of Human-Environment and Geographic Science(HEGS). Her research has been supported by NSF, NASA, DoD, DHS, DOJ, DOE, NOAA, USGS, and NIST. She and her students at the Geospatial Analytics and Innovative Applications (GAIA) Lab explore ways to understand the dynamics of people, events, and places, as well as the connections among brain health, spatial behaviors, and the environment. They also investigate the learning mechanisms taken by humans or machines to conceptualize, represent, and compute geospatial processes.