In addition to my appointment in Geographical and Sustainability Sciences, I am a cluster faculty at Iowa Informatics Initiative (UI3) and a coordinating committee member for the Geoinformatics program.
My research focuses on developing new theories, methodologies and applications to help extract and understand complex patterns from large geo-social networks, i.e., networks embedded in geographic space and time such as migration, human mobility, commodity flows and information flows. Geo-social networks are formed by flows of physical entities (e.g., movements of humans, vehicles, sensors, animals), and communication (e.g., information, ideas, innovation, personal communication) that connect places to places and individuals to individuals. Given the complexity introduced by highly interacting systems of geo-social networks, solving a real-world problem often need to simultaneously consider the geographic, temporal and network components that form the system and relationships among them. For example, disease spread is influenced by many factors such as human mobility, social ties, population dynamics, transportation infrastructure and seasonal changes in weather, and the relationships among these factors. Human migration is driven by not only the availability of jobs or average temperature at a destination place but also the availability of family and friendship ties. During an emergency, knowing how information diffuses among geographic locations and through a network of social actors is crucial for managing situational awareness and assisting emergency management.
My research falls into three major areas:
- Space-time analysis and visualization of big mobility and geo-social networks.
- Big data analytics for social media and networking applications
- Human-computer interaction, and geovisual analytics
To Prospective Graduate Students:
We offer Master's and PhD degrees both at the Department of Geographical and Sustainability Sciences, and the interdisciplinary program at Geoinformatics. Graduate teaching and research fellowships, and assistantships are available for competitive students. Before applying, please contact me with your brief research interests and CV attached. I invite competitive students for a Skype interview. The interview starts with a 6 minute, 40 second, a Pecha Kucha style presentation. Your presentation should focus on your current work, future research goals and interests, and how those intersect with my research agenda.
- Foundations of GIS (GEOG: 1050) - FALL 2017
- Introduction to Geographic Databases (GEOG: 4580) - FALL 2017
- Introduction to Geographic Visualization (GEOG: 3540) - SPRING 2018
- Spatial Analysis and Modeling (GEOG: 6500)
GEOG 3540 Course Website: https://geog3540.github.io/spr2016/
Koylu, C., Delil, S., Guo, D. & Celik, R.N. (2017, In Review) Discovering Functional Regions, Flow Patterns and Their Change over Time: A Longitudinal Analysis of Patient Mobility in Turkey. Transactions in GIS.
Koylu, C. (2017, In Press) Uncovering geo-social semantics from the Twitter mention network: An integrated approach using spatial network smoothing and topic modeling. “Human Dynamics Research in Smart and Connected Communities”, Springer GeoJournal Library Book Series.
Koylu, C. (2017, In Press) Discovering multi-scale community structures from the interpersonal communication network on Twitter. “Agent-Based Models and Complexity Science in the Age of Geospatial Big Data – Selected Papers from GIScience 2016”, Springer.
Koylu, C., & Guo, D. (2016). Design and evaluation of line symbolizations for origin–destination flow maps. Information Visualization, 0(0), 1473871616681375. doi:doi:10.1177/1473871616681375
Koylu, C. (2016). Extracting and Visualizing Geo-Social Semantics from the User Mention Network on Twitter. Proceedings of GIScience 2016 Workshop on Rethinking the ABCs: Agent-Based Models and Complexity Science in the age of Big Data, CyberGIS, and Sensor Networks, Montreal, Canada, September 27, 2016.
Guo, D., Kasakoff, A. B., Koylu, C., Huang, Y., & Grieve, J. (2015) “Historical Population Informatics: Comparing Big Data of Family Trees and the U.S. 1880 Census for Migration Analysis” Population Informatics for Big Data (PopInfo'15) in conjunction with the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) , August 10, 2015, Sydney
Koylu, C., Guo, D., Kasakoff, A., & Adams, J. W. (2014). Mapping family connectedness across space and time. Cartography and Geographic Information Science, 41(1), 14-26 (Featured on the cover)
Koylu, C., & Guo, D. (2013). Smoothing locational measures in spatial interaction networks. Computers, Environment and Urban Systems, 41(0), 12-25. doi: http://dx.doi.org/10.1016/j.compenvurbsys.2013.03.001