Tech Talk: Yingjie Hu

Advancing Spatial and Textual Analysis with GeoAI

Yingjie Hu

University of Buffalo
11:30 a.m. Wednesday, October 21, 2020 | Zoom*

Abstract:

A rich amount of geographic information exists in unstructured texts, such as news articles, web pages, historical archives, and social media posts. Geoparsers are useful tools that extract location mentions from unstructured texts, thereby enabling spatial analysis of big textual data. In this talk, I will present our recent work in designing a unified platform for comparing geoparsers and building a deep learning-based model for improving toponym recognition from social media messages.

Bio:

Yingjie Hu is an Assistant Professor in the Department of Geography at the University at Buffalo (UB) and the National Center for Geographic Information and Analysis (NCGIA). He develops and applies spatial analysis, data mining, machine learning, and deep learning methods to address various geospatial problems in disaster response, public health, urban planning, and digital humanities. He received his Ph.D. from the Department of Geography at the University of California, Santa Barbara, and is an alumnus of the STKO Lab. He holds M.S. and B.S. degrees from East China Normal University. Hu is the author of over 50 peer-reviewed articles in top journals and conferences. He is passionate about teaching and conducting research on GIScience.