Coffee Hour with Yao-Yi Chiang

Enjoy a free catered lunch, a presentation by Yao-Yi Chiang with the Department of Computer Science & Engineering at the University of Minnesota-Twin Cities, and conversation with students, staff, and faculty from the GES Department. Lunch will be available starting at 12:30 p.m. and Yao-Yi Chiang will present from 1-2 p.m. Those joining us for lunch must pre-register. Please RSVP using the event registration link above by the end of the day on Monday, March 18th.  

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 and inconsistencies in their spatiotemporal scales often result in existing analytic 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 Yao-Yi Chiang's research results in Spatial Artificial Intelligence. The talk will first present his recent physics-enabled machine learning methods leveraging spatial science theories for spatiotemporal predictions. This talk will also outline Yao-Yi Chiang's 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 held the position of 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, where he develops machine learning methods to leverage location and time information in data to understand complex environmental phenomena and human-environmental interactions. He works with multi-modal and multi-scale data containing explicit or implicit location and time information, such as traffic, air quality, satellite imagery, images, and text documents, for extracting valuable insights from heterogeneous data and solve real-world problems. Dr. Chiang has received funding from various organizations, including NSF, NIH, DARPA, 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 worked as a research scientist for 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.