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Yao-Yi Chiang

My research interests lie at the intersection of Computer Science and Spatial Science. I build algorithms and applications for acquiring, modeling, fusion, and visualization of spatial information. I work with a group of talented people in USC Spatial Computing.

Current Position

Associate Professor (Research) in Spatial Sciences and Informatics

Spatial Sciences Institute,
University of Southern California

University of Southern California

Chief Scientist


Research Keywords

  • Digital Map Processing
  • Geospatial Data Integration
  • GIScience
  • Artificial Intelligence
  • Image Processing
  • Graphics Recognition
  • Pattern Recognition
  • Document Analysis and Recognition
  • Geographic Information System
  • Data Mining


Yao-Yi Chiang received his Ph.D. degree in Computer Science from the University of Southern California in 2010; his Bachelor degree in Information Management from the National Taiwan University in 2000. His general area of research is artificial intelligence and data science, with a focus on information integration and spatial data analytics. He develops computer algorithms and applications that discover, collect, fuse, and analyze data from heterogeneous sources to solve real world problems. Dr. Chiang is also an expert on digital map processing and geospatial information system (GIS). He has published a number of articles on automatic techniques for geospatial data extraction and integration.

Prior to USC, Dr. Chiang worked as a research scientist for Geosemble Technologies and Fetch Technologies in California. Geosemble Technologies was founded based on a patent on geospatial data fusion techniques, and he was a co-inventor. Geosemble Technologies was acquired by TerraGo and Fetch Technologies was acquired by Connotate, both in 2012.


2005 - Present

Journal Articles
Peer-Reviewed Conference/Workshop Articles

Publication Word Cloud & Venues

Word cloud from my publication

Let's meet at conferences

I am a regular attendee of the ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM GIS), International Conference on Geographic Information Science (GIScience), International Conference on Document Analysis and Recognition (ICDAR), IAPR International Workshop on Graphics RECognition (GREC), and International Conference on Pattern Recognition (ICPR).

Publication frequency by venues

Others 24%

PhD Dissertation


Yao-Yi Chiang, Ph.D. Dissertation, University of Southern California, Sept. 2010 PDF


Raster maps offer a great deal of geospatial information and are easily accessible compared to other geospatial data. However, harvesting geographic features locked in heterogeneous raster maps to obtain the geospatial information is challenging. This is because of the varying image quality of raster maps (e.g., scanned maps with poor image quality and computer-generated maps with good image quality), the overlapping geographic features in maps, and the typical lack of metadata (e.g., map geocoordinates, map source, and original vector data).

Previous work on map processing is typically limited to a specific type of map and often relies on intensive manual work. In contrast, this thesis investigates a general approach that does not rely on any prior knowledge and requires minimal user effort to process heterogeneous raster maps. This approach includes automatic and supervised techniques to process raster maps for separating individual layers of geographic features from the maps and recognizing geographic features in the separated layers (i.e., detecting road intersections, generating and vectorizing road geometry, and recognizing text labels).

The automatic technique eliminates user intervention by exploiting common map properties of how road lines and text labels are drawn in raster maps. For example, the road lines are elongated linear objects and the characters are small connected-objects. The supervised technique utilizes labels of road and text areas to handle complex raster maps, or maps with poor image quality, and can process a variety of raster maps with minimal user input.

The results show that the general approach can handle raster maps with varying map complexity, color usage, and image quality. By matching extracted road intersections to another geospatial dataset, we can identify the geocoordinates of a raster map and further align the raster map, separated feature layers from the map, and recognized features from the layers with the geospatial dataset. The road vectorization and text recognition results outperform state-of-art commercial products, and with considerably less user input. The approach in this thesis allows us to make use of the geospatial information of heterogeneous maps locked in raster format.


Ching-Chien Chen, Craig A. Knoblock, Cyrus Shahabi, Yao-Yi Chiang, Automatically and Accurately Conflating Road Vector Data, Street Maps, and Orthoimagery United States Patent 20070014488


I teach subjects in Spatial Sciences, Computer Science, and Data Informatics at University of Southern California

Spatial Databases

SSCI-582, USC Geographic Information Science and Technology (GIST)

GIS Programming and Customization

SSCI-586, USC Geographic Information Science and Technology (GIST)

Geospatial Data Integration

CSCI-599, USC Computer Science

Mobile GIS

SSCI-592, USC Geographic Information Science and Technology (GIST)

  • Spatial technology opens a window into history

    Computer scientist builds software to help scholars enrich their research with historical maps. Lizzie Hedrick, FEBRUARY 9, 2016
  • Best Vision Paper, First Place (2015 ACM SIGSPATIAL)

    The 2015 ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (award sponsored by the Computing Research Association's Computing Community Consortium under the CCC Blue Sky initiative)
  • Certified GIS Professional, 2015

    The GIS Certification Institute (GISCI)
  • Best Paper Award, Second Place, the Forth Annual Intelligent Systems Division Graduate Student Symposium, 2008

    Information Sciences Institute, University of Southern California
  • Best Paper Award, Second Place, the Forth Annual Intelligent Systems Division Graduate Student Symposium, 2009

    Information Sciences Institute, University of Southern California
  • The Viterbi School Doctoral Fellowship, 2007 - 2010

    Viterbi Engineering School, University of Southern California

Research Notes

Under Construction

Contact Information

I have been working with USC undergraduate and graduate students (in Computer Science, Geographic Information Science and Technology, and GeoDesign) on credit or no-credit direct research effort. Please feel free to contact me if you are interested to work on one of our projects.

Take a look at our group page here.

Phone : +1(213) 740-5910

Address : 3616 Trousdale Parkway, AHF B55, Spatial Sciences Institute, University of Southern California, Los Angeles, CA 90089-0374

Email : yaoyichi_at_gmail_dot_com