معرفی
Hanan Samet is a Distinguished University Professor at the University of Maryland's Computer Science Department, affiliated with the Institute for Advanced Computer Studies (UMIACS) and the Center for Automation Research. He holds a Ph.D. from Stanford University (1975) and specializes in spatial databases, data structures, and geographic information systems. His research bridges computer science and geospatial analytics, with applications in image databases, computer vision, and spatio-temporal data management.
Education:
- Ph.D., Computer Science, Stanford University, 1975
Research Interests: Focuses on spatial data structures, GIS, spatio-textual systems like NewsStand and CoronaViz, trajectory analysis, and metric indexing. His work emphasizes scalable algorithms for spatial networks and multimedia databases.
Notable Projects:
- CoronaViz: Tracks disease spread via spatio-temporal data visualization
- NewsStand: Maps news articles geospatially
- SAND: Spatial browser for digital government
Awards: ACM Paris Kanellakis Award (2014), IEEE McDowell Award (2015), UCGIS Research Award, and Fellowships in ACM/IEEE/AAAS. Recognized for advancing spatial database theory and practice.
Grants/Advising: Leads NSF-funded projects on spatio-textual extraction and similarity search. Advises graduate students (e.g., Nicole Schneider, Montana Hoover) and undergraduate researchers.
Labs/Teams: Active in UMIACS and the Center for Automation Research, collaborating on projects like VASCO (spatial visualization tools) and MARCO (image database systems).
