CS&E Colloquium: Yao-Yi Chiang
This week's speaker, Yao-Yi Chiang (University of Minnesota), will be giving a talk titled, "Spatial AI and Its Applications in an Interdisciplinary World".
Knowing what has happened, where and when, and how it has changed over space and time is the key to modeling complex spatiotemporal phenomena and understanding how humans depend on, adapt, and modify them. Today, many disciplines produce and use an increasing volume of data containing location and time information, either explicitly, e.g., mobility data, air quality data, satellite imagery, or implicitly, e.g., scanned historical maps and text documents. However, the substantial heterogeneity in these data coupled with inconsistencies in their spatiotemporal scales often result in existing methods focusing on a few data sources and treating the space and time dimensions as an afterthought, limiting their capability to solve critical problems. This talk will present recent highlights of our research results in Spatial Artificial Intelligence. The talk will present machine learning methods leveraging spatial science theories for predicting spatiotemporal phenomena and building a spatial language model to facilitate geospatial entity typing and linking. This talk will also outline our ongoing research directions in Spatial AI and interdisciplinary impact in public health, transportation, national security, geography, history, library, and digital humanities.
Dr. Yao-Yi Chiang is an Associate Professor in the Computer Science & Engineering Department at the University of Minnesota. Previously, he was an Associate Professor (Research) in Spatial Sciences at the University of Southern California. Dr. Chiang is an Action Editor of GeoInformatica (Springer) and an editorial board member for Transactions in GIS (Wiley). He earned his Ph.D. in Computer Science from the University of Southern California and his bachelor's degree in Information Management from the National Taiwan University. Dr. Chiang's research interests are in spatial artificial intelligence. He develops machine learning methods to understand complex spatiotemporal phenomena and how humans interact with these phenomena using multimodal multiscale data that can be sparse, and unevenly distributed in space and time. Dr. Chiang has received funding from various organizations, including NSF, NIH, DARPA, IARPA, NGA, NEH, and industry partners such as NTT Global Networks, BAE Systems, Conveyancing Liability Solutions, TerraGo, and Rumsey Map Collection. He has also worked as a visiting researcher at Google AI in New York City and a machine learning consultant at the Spatial Computing Group at Meta. Before pursuing his Ph.D., Dr. Chiang was a research scientist at Geosemble Technologies and Fetch Technologies in California, where he co-invented a patent on geospatial data fusion techniques. Dr. Chiang is also the founder of Kartta Foundation, a non-profit organization that provides software and services to distill and assemble geographic knowledge for the public good. Kartta Foundation manages Kartta Labs, a previous Google product, including re.city.