De Floriani, Leila

Bio

​​​​​​​Leila De Floriani is a full professor at the University of Maryland with a joint appointment with the Department of Geographical Sciences and the University of Maryland Institute for Advanced Computer Studies  (UMIACS).  She is affiliated with the Department of Computer Science, the Center for Geospatial Information Science, and the UMIACS Center for Automation Research.  Since the Fall of 2021, she is the Director of Graduate Studies in Geographical Sciences. 

De Floriani has previously been a professor of Computer Science at the University of Genova (Italy), where she developed the first undergraduate and graduate curricula in computer graphics in Italy, and served as Director of the Ph.D. program in Computer  Science for eight years. She has also held positions at the University of Nebraska, Rensselaer Polytechnic Institute, and the Italian National Research Council.

She is a Fellow of IEEE, a Fellow of the International Association for Pattern Recognition (IAPR), a Fellow of the Eurographics Association, a Pioneer of the Solid Modeling Association, and an inducted member of the IEEE Visualization Academy. She is a recipient of the IEEE Computer Society Golden Core award and an inducted member of the IEEE Honor Society IEEE Eta Kappa Nu.

De Floriani was the 2020 President of the IEEE Computer Society. She is the IEEE Division VIII Director for 2023-24 and a member of the IEEE Board of Directors and the IEEE Assembly. Among the other involvements, she has been a member of the IEEE Conferences Committee (2021-23), and of the IEEE Publication Services and Products Board (2023). She also joined the Computing Research Association (CRA) Board in 2020-23. She is a member of the Scientific Council of the Italian Scientists and Scholars in North America Foundation (ISSNAF).

De Floriani has been the editor-in-chief of the IEEE Transactions on Visualization and Computer Graphics (TVCG) from 2015 to 2018 and served as an associate editor for IEEE TVCG from 2004 to 2008. De Floriani is currently an editor of the ACM Transactions on Spatial Algorithms and Systems, Computers & Graphics, Computer Science Review, GeoInformatica, Graphical Models, and the International Journal of Spatial Information Science. She has served on the program committees of over 150 leading international conferences, contributing to several of them in a leadership capacity.

She has authored over 300 peer-reviewed scientific publications in data visualization, spatial data science, computer graphics, geometric modeling, shape analysis and understanding, garnering several best paper awards and invitations as a keynote speaker. Her research has been funded by numerous national and international agencies, including the European Commission, the National Science Foundation, and NASA.

Please see my academic web page at http://www.umiacs.umd.edu/~deflo/ for further information.

Featured Faculty Profile: "Woman in Science: The Groundbreaking Path of Professor Leila De Floriani"

Areas of Interest

  • Geospatial data visualization
  • Topology-based data visualization
  • Spatial data structures
  • Spatial big data representation and analysis
  • Terrain modeling and analysis
  • Topological data analysis
  • Geometric modeling and processing

Research Topics

GEOG 470/770/CMSC 401: Algorithms for Geospatial Computing 

Usually offered in the Spring semester

Course Description:

  • Introduction to fundamental geometric algorithms for spatio- temporal data processing and analysis. 
  • Managing and clustering point clouds for processing and analysis of LiDAR data. 
  • Terrain modeling: representations, query algorithms, visibility and morphological analysis. 
  • Applications: terrain reconstruction, urban modeling, forest management and coastal data management and analysis 
  • Algorithms for road network analysis and reconstruction. 
  • Scalable algorithms and representations for big geospatial data. 

Course Learning Objectives

Upon a successful completion of the course the students will be able to: 

  • Acquire in-depth knowledge of fundamentals of algorithms for geospatial data science. 
  •  Learn techniques for efficiently encoding, manipulating and querying geospatial data. 
  • Gain substantial understanding of how geospatial data are actually processed in modern geographical information systems. •
  • Learn how to design, use and implement algorithms dealing with geospatial data, with emphasis on point data processing and analysis, on terrain modeling and on road network analysis. 
  • Apply algorithms for discrete and continuous geospatial data to LiDAR data processing and analysis, and algorithms for road network routing and reconstruction to real-world data sets 
  • Learn how to use open-source software to solve geospatial data analysis problems
  • Xu, Xin, Federico Iuricich, and Leila De Floriani. "A topology-based approach to individual tree segmentation from airborne LiDAR data." GeoInformatica (2023): 1-30.
    • Xu, Xin, Federico Iuricich, Kim Calders, John Armston, and Leila De Floriani. "Topology-based individual tree segmentation for automated processing of terrestrial laser scanning point clouds."
      • Song, Y., Fellegara, R., Iuricich, F., & De Floriani, L. (2021). Efficient topology-aware simplification of large triangulated terrains. In GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems (Vol. 1, Issue 1)

        • Leila De Floriani headshot

        Leila De Floriani
        Professor and Graduate Director

        | 1135 LeFrak Hall

        | deflo@umd.edu

        Media Availability  No