Biography

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

She has previously been a professor 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. During her career, she has also held positions at the University of Nebraska, at Rensselaer Polytechnic Institute, and at the Italian National Research Council.

De Floriani was the 2020 President of the IEEE Computer Society. She is a member of the Board of Governors of the IEEE Computer Society since 2017. She currently serves as the founding Chair of the IEEE Computer Society Diversity and Inclusion Committee. She is a member of the Computing Research Association (CRA) Board, and of the IEEE Conferences and Conference Publications Committees.

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 she is an inducted member of the IEEE Honor Society IEEE Eta Kappa Nu.

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

De Floriani has authored over 300 peer-reviewed scientific publications in data visualization, spatial data representation and processing, 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 and the National Science Foundation.


Contacts

deflo(at)umd.edu

(301) 405-4391 or (301) 405-6584

Awards & Honors

  • Fellow, International Association for Pattern Recognition (IAPR) for contributions to geometric modeling and image analysis, 1998.
  • Fellow, IEEE for contributions to geometric modeling and scientific visualization, 2016.
  • Recipient, Solid Modeling Pioneer Award for seminal work in solid and feature-based modeling, 2017.
  • Recipient, IEEE Computer Society Golden Medal Award, 2018.
  • Inducted Member, IEEE Honor Society IEEE-HKN for excellence in education and meritorious work in geometric modeling and scientific visualization, 2019.
  • Fellow, Eurographics Association, for outstanding contributions, leadership and service to the fields of Computer Graphics, Visualization and to the Eurographics Association in particular, and for foundational contribution to starting up one of the most vital research communities in Geometry and Graphics in Italy, 2020.
  • Inducted Member, IEEE Visualization Academy, 2020.
  • Best paper awards at Shape Modeling International (2015), IEEE/EG Symposium on Volume and Point-Based Graphics (2008), ACM SIGSPATIAL (2008); best paper runner up at ACM SIGSPATIAL 2020.

Recent News

  • Leila De Floriani

    • Elected as IEEE 2022 Division VIII Director Elect and 2023-2024 Division VIII Direct. Read more.
    • 2020 President / 2021 Past President, IEEE Computer Society.
    • Founding Chair, IEEE Computer Society Diversity and Inclusion Committee, 2021.
    • Keynote talk, Representations and topology-based clustering methods for spatial data analysis and visualization, IEEE International Conference on Communication and Green Engineering (CCGE21), September 23, 2021.
    • Lighting talk at UMD-NASA/Goddard AI/ML Workshop, on "Representations and topology-based methods for geospatial data analysis",September 22nd, 2021.
    • Invited talk, Diversity and Inclusion Talk (DIT) Series, Women of Engineering, IEEE Bangladesh Section, October 14, 2021.
    • Member, IEEE Returning Mothers Conference Advisory Committee, since July 2021.
    • Participant, Round Table on "Diversity and Inclusion - Efforts and Impacts", IEEE Returning Mothers Conference, August 27, 2021.
    • Associate Editor, Computer Science Review, appointed in April 2021.
    • Associate Editor, Computers & Graphics, appointed in April 2021.
    • Speaker, Computer Society President Panel, COMPSAC 2021.
  • Our paper on "Efficient topology-aware simplification of large triangulated terrains" by Yunting Song, Riccardo Fellegara, Federico Iuricich, and Leila De Floriani has been accepted at ACM SIGSPATIAL 2021. | Video
  • Haoan Feng joins the University of Maryland as PhD student and the group, August 2021.

  • Zachary Burnett joins the University of Maryland as PhD student and the group, August 2021.

  • Yuehui Qian joins the University of Maryland as PhD student and the group, August 2021.

2020 News

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  • Leila De Floriani

    • Elevated to Fellow of the European Graphics (Eurographics), Association, May 2020.
    • Inducted as Member the IEEE Visualization Academy, October 2020.
    • General Co-Chair, Computational Visual Media Conference, Macao, 2020.
    • Member, Computing Research Association Board, appointed in January 2020.
    • Invited Talk. Topology-based clustering methods for geospatial data analysis, IEEE Vardhaman College of Engineering and IEEE Hyderabad Section, August 2020.
    • Invited talk, Topology-based approaches to data analysis, IEEE YESIST12 , August 2020.
    • Invited talk, Topology-based approaches to data visualization, Women in Engineering, Global Summit 2020, November 2020.
    • Invited talk, Mesh-based approached to modeling point clouds for geospatial applications, IEEE Computer Society Japan Chapter, December 2020.
    • Invited talk, Diversity and Inclusion Activities in the IEEE Computer Society, Women in Engineering International Leadership Summit, December 2020.
  • Yunting Song is awarded the GIS Summer Research Fellowship by the Department of Geographical Sciences, University of Maryland, May 2020.

  • Paper entitled “A Persistence-Based Approach for Individual Tree Mapping” by Xin Xu, Federico Iuricich and Leila De Floriani was awarded the best paper runner-up at ACM SIGSPATIAL 2020.

  • Ulderico Fugacci appointed as tenured research scientist at the Italian National Research Council, Genova July 2020.

  • Sara Scaramuccia got a postdoc position at the Department of Mathematics, Polytechnic University of Torino (Italy), September 2020.

2019 News

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  • Leila De Floriani

    • 2019 President-Elect of the IEEE Computer Society.
    • Invited Speaker at United States-Japan Natural Resources Panel on Aquaculture, December 2019.
    • Inducted as professional member of the IEEE Honor Society Eta-Kappa-Nu, November 2019.
    • Recipient of a 2019 Certificate Appreciation from IEEE Computer Society, October 2019.
    • Keynote Speaker, Topology-based approaches for large field data analysis, 2019 International Workshop on Geocomputation for Social Sciences and Intelligent Geospatial Information Service, Wuhan University, July 2019.
  • Riccardo Fellegara got a senior scientist position at the German Aerospace Agency, Braunsweig, Germany.

  • Ulderico Fugacci got a postdoc position at the Department of Mathematics, Polytechnic University of Torino, Italy.

  • Sara Scaramuccia got a postdoc position at Nice University.

2018 News

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  • Leila De Floriani
    • Talk at Dagstuhl seminar on Foundations of Data Visualization (January 21-26 , 2018): Topological data analysis and topology-based visualization.
    • Invited talk, University of Genova (Italy) March 2018: Spatial data analysis and visualization through topological techniques.
    • Keynote speaker at the International Symposium CompIMAGE’18 (Cracow, Poland, July 2-5, 2018): Topology-based approaches for scientific data visualization.
    • Invited speaker at the Peking Visualization School (Peking University, China), Jul 17, 2018: Fundamentals of topology-based data visualization.
    • Invited talk, Tianjin University (China), July 18, 2018, Topology-based visual analytics: an overview.
    • Panelist at ChinaVis 2018 on “The Opportunity and Challenges of Visualization in the New Era”, July 26, 2018.
  • Sara Scaramuccia defended her PhD on May 23, 2018
  • Federico Iuricich got a tenure-track position as Assistant Professor at Clemson University, USA

Meet the Team

Principal Investigator

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Leila De Floriani

Professor

Graduate Students

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Xin Xu

PhD student

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Yunting Song

PhD student

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Noel Dyer

PhD student

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Haoan Feng

PhD student

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YueHui Qian

PhD student

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Zachary Ramesh Burnett

PhD student

Collaborators

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Federico Iuricich

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Riccardo Fellegara

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Kenneth Weiss

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Paola Magillo

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Sara Scaramuccia

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Ulderico Fugacci

Publications

Quickly discover relevant content by filtering publications.
TopoCluster: A Localized Data Structure for Topology-based Visualization
Efficient topology-aware simplification of large triangulated terrains
A Persistence-Based Approach for Individual Tree Mapping
Computing multiparameter persistent homology through a discrete Morse-based approach
Efficient Homology-Preserving Simplification of High-Dimensional Simplicial Shapes
Tetrahedral trees: a family of hierarchical spatial indexes for tetrahedral meshes
Computing Discrete Morse Complexes from Simplicial Complexes
Triangulated Irregular Network
Efficient Representation and Analysis of Triangulated Terrains
A Discrete Morse-based Approach to Multivariate Data Analysis

Professional Services

Editorial Boards

  • Editor-in-Chief, IEEE Transactions on Visualization and Computer Graphics (TVCG), 2015-2018.
  • Associate Editor, ACM Transactions on Spatial Algorithms and Systems, 2013-present.
  • Associate Editor, Graphical Models, 2010-present.
  • Associate Editor, Computers & Graphics, 2019-present.
  • Editorial Board Member, GeoInformatica, Springer, 2004-present.
  • Editorial Board Member, International Journal of Spatial Information Science, 2014-present.
  • Editorial Board Member, International Journal of Geo-Information, 2019-present.
  • Editorial Board Member, Computer Science Review, 2021.
  • Associate Editor, IEEE Transactions on Visualization and Computer Graphics, 2004-2008.
  • Editorial Board Member, International of Journal of Geographic Information Systems, 1990-1998.
  • Editorial Board Member, Computer-Aided Design, 1990-1996.

Conferences

  • Program Committee Senior Member, ACM/SIGSPATIAL Conference on Geographic Information Systems (2021).
  • Program Committee Member, International Conference on Shape Modeling (SMI 2021).
  • Program Committee Member, International Conference on Visualization (VIS 2021).
  • General Co-Chair, Computational Visual Media Conference, Macao, 2020.
  • Program Committee Senior Member, ACM/SIGSPATIAL Conference on Geographic Information Systems (2020).
  • Program Committee Member, International Conference on Shape Modeling (SMI 2020).
  • Program Committee Member, International Conference on Visualization (VIS 2020).
  • Chair, Best Paper Award Committee, IEEE VIsualization, 2019.
  • Member, Steering Committee, International ACM SIGMOD Workshop on Managing and Mining Enriched Geo-Spatial Data, since 2019.
  • Member, Steering Committee, EnvirVis - Visualization in Environmental Sciences Workshop, since 2016.
Read more
  • Member, Steering Committee, GeoRich.
  • Member, Steering Committee, EnvirVis.
  • Chair, Best Paper Award Committee, SciVis, 2019.
  • Program Committee Member, IEEE Visualization (2019).
  • Program Committee Senior Member, ACM/SIGSPATIAL Conference on Geographic Information Systems (2019).
  • Program Committee Member, International Conference on Shape Modeling (SMI 2019).
  • Program Committee Senior Member, ACM/SIGSPATIAL Conference on Geographic Information Systems (2018).
  • Program Committee Member, International Conference on Shape Modeling (SMI 2018).
  • Program Committee Member, 10th International Conference on Geographic Information Science (GIScience 2018).
  • Program Committee Member, 18th International Workshop on Combinatorial Image Analysis (IWCIA 2018).
  • Program Committee Member, International Conference on Shape Modeling (SMI 2017).
  • Program Committee Senior Member, ACM/SIGSPATIAL Conference on Geographic Information Systems (2017).
  • Program Committee Member, 17th International Workshop on Combinatorial Image Analysis (IWCIA 2016).
  • Program Committee Member, International Conference on Shape Modeling (SMI 2016). Program Committee Senior Member, ACM/SIGSPATIAL Conference on Geographic Information Systems (2016).
  • Program Committee Member, Eurographics Conference (2016).
  • Program Committee Member, 9th International Conference on Geographic Information Science (GIScience 2016).
  • Track Chair, International Conference on Image Analysis and Processing (2015).
  • Program Committee Member, International Conference on Shape Modeling (SMI 2015). Program Committee Senior Member, ACM/SIGSPATIAL Conference on Geographic Information Systems (2015).
  • Program Committee Member, International Conference on Shape Modeling (SMI 2015).
  • Program Committee Member, AGILE International Conference on Geographic Information Science (2014).
  • Program Committee Member, 8th International Conference on Geographic Information Science (GIScience 2014).
  • Program Committee Member, 17th International Workshop on Combinatorial Image Analysis (IWCIA 2014).
  • Program Committee Senior Member, ACM/SIGSPATIAL Conference on Geographic Information Systems (2014).
  • Program Committee Member, International Conference on Image Analysis and Processing (2013).
  • Program Committee Member, International Conference on Shape Modeling (SMI 2013). Program Committee Senior Member, ACM/SIGSPATIAL Conference on Geographic Information Systems (2013).
  • Program Committee Member, Joint IEEE/ Eurographics Conference on Visualization (Eurovis), 2013.
  • Program Committee Member, AGILE International Conference on Geographic Information Science (2012).
  • Program Committee Member, IEEE Visweek 2012.
  • Program Committee Member, Eurographics Conference (2012).
  • Program Committee Member, International Conference on Shape Modeling (SMI 2012). Program Committee Senior Member, ACM/SIGSPATIAL Conference on Geographic Information Systems (2013).
  • Program Committee Member, 8th International Conference on Geographic Information Science (GIScience 2012).
  • Program Committee Member, ACM/EUROGRAPHICS Symposium on Geometry Processing (2012).
  • Program Committee Member, 9th ACM/EUROGRAPHICS Symposium on Geometry Processing (2011).
  • Program Committee Member, 18th ACM Conference on Geographic Information Systems (2011).
  • Program Committee Member, International Conference on Image Analysis and Processing (2011).
  • Program Committee Member, IEEE Visweek 2011.
  • Program Committee Member, ACM-SIAM Conference on Solid and Physical Modeling (2011).
  • Program Committee Member, AGILE International Conference on Geographic Information Science (2011).
  • Program Committee Member, ACM/SIGSPATIAL Conference on Geographic Information Systems (2011).
  • Program Committee Member, International Conference on Shape Modeling (SMI 2011).
  • Program Committee Member, 8th ACM/EUROGRAPHICS Symposium on Geometry Processing (2010).
  • Program Committee Member, 18th ACM Conference on Geographic Information Systems (2010).
  • Program Committee Member, International Conference on Shape Modeling (SMI 2010).
  • Program Committee Member, IEEE Visweek 2010.
  • Program Committee Member, 6th International Conference on Geographic Information Science (GIScience 2010).
  • Program Committee Member, Computer Graphics International, 2010.
  • Program Committee Member, 7th ACM/EUROGRAPHICS Symposium on Geometry Processing (2009).
  • Program Committee Member, International Conference on Image Analysis and Processing (2009).
  • Program Committee Member, 13th International Workshop on Combinatorial Image Analysis (IWCIA 2009).
  • Program Committee Member, International Conference on Shape Modeling (SMI 2009).
  • Program Committee Member, ACM Symposium on Solid and Physical Modeling (2009).
  • Program Committee Member, Workshop on Computational Topology in Image Context (2009).
  • Program Committee Member, International Conference on Computer Science and Information Technology (COSIT 2009).
  • Program Committee Member, 17th ACM Conference on Geographic Information Systems (2009).
  • Program Committee Member, International Conference on Shape Modeling (SMI 2008).
  • Program Committee Member, ACM Symposium on Solid and Physical Modeling (2008).
  • Program Committee Member, Pacific Graphics (2008).
  • Program Committee Member, Eurographics Conference (2008).
  • Program Committee Member, 16th ACM Workshop on Geographic Information Systems (2008).
  • Program Committee Member, 6th ACM/EUROGRAPHICS Symposium on Geometry Processing (2008).
  • Program Committee Member, International Conference on Geographic Information Science (GIScience 2008).
  • Program Committee Member, IEEE Conference on 3D Data Processing and Transmission (2008).
  • Program Committee Member, Computer Graphics International (2008).
  • Program Committee Member, International Conference on Computer Graphics Theory and Applications (2008).
  • Program Committee Member, Workshop on Volume Graphics (2008).
  • Co-Chairperson, International Symposium on Shape Modeling and Reasoning for Industrial and Biomedical Applications (2007).
  • Program Committee Member, Computer Graphics International (CGI 2007).
  • Program Committee Member, 15th ACM Conference on Geographic Information Systems (2007).
  • Program Committee Member, International Conference on Shape Modeling (SMI 2007).
  • Program Committee Member, ACM Symposium on Solid and Physical Modeling (2007).
  • Program Committee Member, IEEE Visualization Conference (2007).
  • Program Committee Member, Eurographics Conference (2007).
  • Program Committee Member, 5th ACM/EUROGRAPHICS Symposium on Geometry Processing (2007).
  • Program Committee Member, Workshop on Volume Graphics (2007).
  • Program Committee Member, International Conference on Computer Graphics Theory and Applications (2007).
  • Program Committee Member, 10th AGILE International Conference on Geographic Information Science (2007).
  • Program Committee Member, International Conference on Computer Science and Information Technology (COSIT 2007).
  • Program Committee Member, 14th ACM Conference on Geographic Information Systems (2006).
  • Program Committee Member, International Conference on Shape Modeling (SMI 2006).
  • Program Committee Member, ACM Symposium on Solid and Physical Modeling (2006).
  • Program Committee Member, Digital Geometry and Computer Imagery (DGCI 2005).
  • Program Committee Member, 4th ACM/EUROGRAPHICS Symposium on Geometry Processing (2006).
  • Program Committee Member, International Conference on Spatial Data Handling (SDH 2006).
  • Program Committee Member, International Conference on Computer Graphics Theory and Applications, 2006.
  • Program Committee Member, International Conference on Geographic Information Science (GIScience 2006).
  • Program Committee Member, International Conference on Digital Geometry for Computer Imagery (DGCI 2006).
  • Program Committee Member, Workshop on Volume Graphics (2006).
  • Program Committee Member, GISPLANET 2005.
  • Program Committee Member, International Conference on Shape Modeling (SMI 2005).
  • Program Committee Member, ACM Symposium on Solid and Physical Modeling (2005).
  • Program Committee Member, Digital Geometry and Computer Imagery (DGCI 2005).
  • Program Committee Member, ISPRS Workshop on Dynamic and Multi-dimensional GIS (DMGIS 05).
  • Program Committee Member, International Conference on Image Analysis and Processing (ICIAP 05).
  • Program Committee Member, Computer Graphics International (CGI 2005).
  • Program Committee Member, 12th International Conference on Image Analysis and Processing (2005).
  • Program Committee Member, 13th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG 2005).
  • Program Committee Member, 13th ACM Workshop on Geographic Information Systems (2005).
  • Program Committee Member, 7th International Conference on Spatial Information Theory (COSIT 2005).
  • Program Committee Member, Workshop on Semantic Visual Environments (2005).
  • Program Committee Member, 3rd ACM/EUROGRAPHICS Symposium on Geometry Processing (2005).
  • Program Committee Member, Pacific Graphics (2005).
  • Program Committee Member, 12th ACM Conference on Geographic Information Systems (2004).
  • Program Committee Member, International Conference on Spatial Data Handling (SDH 2004).
  • Program Committee Member, International Conference on Geographic Information Science (GIScience 2004).
  • Program Committee Member, International Conference on Pattern Recognition (ICPR 2004).
  • Program Committee Member, International Conference on Shape Modeling (SMI 2004).
  • Program Committee Member, 2nd ACM/EUROGRAPHICS Symposium on Geometry Processing (2004).
  • Program Committee Member, 2nd Symposium on 3D Data Processing, Visualization and Transmission (2004).
  • Program Committee Member, ACM Symposium on Solid Modeling and Applications (2004).
  • Program Committee Member, 11th ACM Conference on Geographic Information Systems (2003).
  • Program Committee Member, 12th International Conference on Image Analysis and Processing (2003).
  • Program Committee Member, IEEE Visualization Conference (2003).
  • Program Committee Member, International Conference on Spatial Data Handling (SDH 2003).
  • Program Committee Member, International Conference on Geographic Information Science (GIScience 2003).
  • Program Committee Member, First ACM/EUROGRAPHICS Symposium on Geometry Processing (2003).
  • Program Committee Member, 10th ACM Workshop on Geographic Information Systems (2003).
  • Program Committee Member, International Conference on Spatial Data Handling (SDH 2002).
  • Program Committee Member, IEEE Visualization Conference (2002).
  • Program Committee Member, International Conference on Geographic Information Science (GIScience 2002).
  • Program Committee Member, International Conference on Shape Modeling (SMI 2002).
  • Program Committee Member, Joint Eurographics - IEEE VGTC Symposium on Visualization (2002).
  • Program Committee Member, 1st Symposium on 3D Data Processing, Visualization and Transmission (2002).
  • Program Committee Member, International Conference on Pattern Recognition (ICPR 2002).
  • Program Committee Member, 5th International Conference on Spatial Information Theory (2001).
  • Program Committee Member, 4th International Workshop on Visual Form (2001).
  • Program Committee Member, 1st International Symposium on Digital Earth Moving (2001).
  • Program Committee Member, IEEE Visualization Conference (2001).
  • Program Committee Member, International Conference on Geographic Information Science (GIScience 2001).
  • Program Committee Member, International Conference on Shape Modeling (SMI 2001).
  • Program Committee Member, 11th International Conference on Image Analysis and Processing (2001).
  • Program Committee Member, IEEE Conference on Visualization (2000).
  • Program Committee Member, International Conference on Geographic Information Science (GIScience 2000).
  • Program Committee Member, 4th International Conference on Spatial Information Theory (1999).
  • Program Committee Member, 6th International Symposium on Large Spatial Data Bases (1999).
  • Program Committee Member, Eurographics Conference (1999).
  • Program Committee Member, 10th International Conference on Image Analysis and Processing (1999).
  • Program Committee Member, IEEE Conference on Visualization (1999).
  • Program Committee Member, 6th ACM Workshop on Geographic Information Systems (1998).
  • Program Committee Member, 3rd International Conference on Spatial Information Theory (1997).
  • Program Committee Member, 5th International Symposium on Large Spatial Data Bases (1997).
  • Program Committee Member, 5th Workshop on Algorithms and Data Structures (1997).
  • Program Committee Member, International Conference on Urban, Regional and Environmental Planning (1997).
  • Program Committee Member, 9th International Conference on Image Analysis and Processing (1997).
  • Program Committee Member, 3rd International Workshop on Visual Form (1997).
  • Program Committee Member, International Conference on Urban, Regional and Environmental Planning (1996).
  • General Chairperson, 8th International Conference on Image Analysis and Processing (1995).
  • Program Committee Member, 3rd ACM Workshop on Geographic Information Systems (1995).
  • Program Committee Member, International Symposium on Scientific Visualization (1995).
  • Program Committee Member, 2nd International Conference on Spatial Information Theory (1995).
  • Program Committee Member, 4th International Symposium on Large Spatial Data Bases (1995).
  • Program Committee Member, SAC’94: Workshop on GIS (Geographical Information Systems). (1994).
  • Program Committee Member, Second International Workshop on Visual Form (1994).
  • Co-Chairperson, Italy/Israel Symposium on Computer Vision (1991).
  • Program Committee Member, 1st International Conference on Spatial Information Theory (1993).
  • Program Committee Member, Seventh International Conference on Image Analysis and Processing (1993).
  • Program Committee Member, 1st International Workshop on Visual Form (1991).
  • Program Committee Member, 6th International Conference on Image Analysis and Processing (1991).
  • Co-Chairperson, Italy/Israel Symposium on Computer Vision (1991).
  • Program Committee Member, 5th International Conference on Image Analysis and Processing (1989).
  • Program Committee Member, International Conference on Computer Graphics, PIXIM 88 (1988).

IEEE Activities

  • 2022 IEEE Division VIII Director-Elect.
  • 2023-2024 IEEE Division VIII Director.
  • 2020 President, IEEE Computer Society.

  • Member, IEEE Conferences Committee, 2021-2023.
  • Member, IEEE Conference Publications Committee, 2021.
  • Member, IEEE Conference Diversity Best Practices Ad-Hoc Committee, 2021.
  • Member, IEEE Conference Open Access Ad-Hoc Committee, 2021.
  • Member, IEEE Technical Activities Board, 2020.
  • Member, IEEE USA Research and Development Policy Committee, 2020.

  • Founding Chair, IEEE Computer Society Diversity and Inclusion Committee, 2021.
  • Chair, IEEE Computer Society Intersociety Cooperation Committee, 2021.
  • Chair, IEEE Computer Society Nominations Committee, 2021.
  • IEEE Computer Society Liaison, Computing Research Association Board, since 2020.
  • Chair, IEEE Computer Society Diversity and Inclusion Task Force, 2020.
  • Chair, IEEE Computer Society Board of Governors, 2020.
  • Chair, IEEE Computer Society Executive Committee, 2020.
  • Chair, IEEE Computer Society Executive Committee, 2020.
  • Chair, IEEE Computer Society Constitution and Bylaws Committee, 2019.
  • Member, IEEE Computer Society Board of Governors, since 2017.
  • Member, IEEE Computer Society Intersociety Cooperation Committee, since 2019.
  • Member, IEEE Computer Society Finance Committee, since 2019.
  • Member, IEEE Computer Society Nominations Committee, 2019.
  • Member, IEEE Computer Society Executive Committee, since 2019.
  • Chair, IEEE Computer Society Audit Committee, 2018.
  • Vice-Chair, IEEE Computer Society Fellow Evaluation Committee, 2017-2018.
  • Member, IEEE Computer Society Constitution and Bylaws Committee, since 2018.
  • Member, IEEE Computer Society Audit Committee, 2017.
  • Member, IEEE Computer Society Board of Governors, since 2017.
  • Member, IEEE Computer Society Transactions Operations Committee, 2015-2018.
  • Member, (non-voting), IEEE Computer Science Publication Board, 2015-2018.
  • Member, IEEE Computer Society Fellow Evaluation Committee, 2016.
  • Member, IEEE Computer Society Ad-hoc Growth Committee, 2018.
  • Member, IEEE Computer Society Transactions on Visualization and Computer Graphics Editor-in-Chief Search Committee, 2018.
  • Member, Executive Committee, IEEE Computer Society Visualization and Graphics Technical Committee (VGTC), 2015-2018.

  • Fellow, IEEE.
  • Member, IEEE Computer Society.
  • Member, IEEE Geoscience and Remote Sensing Society.
  • Member, IEEE Women in Engineering.
  • Member, IEEE Computer Society Visualization and Graphics Technical Committee.
  • Member, IEEE Computer Society Pattern Analysis and Machine Intelligence Technical Committee.

Teaching

Algorithms for Geospatial Computing

GEOG 470/770 - CMSC 498Q

  • Instructor: Professor Leila De Floriani
  • E-mail: deflo(at)umd.edu
  • Offered in Spring 2022: Tuesdays and Thursdays: 12:30pm – 1:45pm
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.

Prerequisites: Some programming background in Python or C++ is required for this course (see the course syllabus)

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
Course communication and material
  • Communication through Canvas within the University of Maryland Enterprise Learning Management System (ELMS)):
  • Instructor: post course slides, and notes, assignments and grades
  • Students: turn in assignments and projects
  • Material:
    • Course notes in the form of slides posted on Canvas
    • Recording of the classes
    • Recommended books
  • N. Xiao, GIS Algorithms, 2016, SAGE Publications
  • M.J. de Smith, M.F. Goodchild, P.A. Longley, Geospatial Analysis: A Comprehensive Guide to Principles, Techniques and Software Tools (sixth edition), 2018.
  • M. F. Worboys, M. Duckham, GIS: A Computing Perspective, 2004, CRC Press.
  • M. Goodrich, R. Tamassia, M.H. Goldwasser, Data Structures and Algorithms in Python, 2013, Wiley and Sons (for Python programming)

Please see the Spring 2022 Syllabus for more information.

Research

Major research contributions

  • Hierarchical models for graph representation and analysis.
  • Mesh-based multi-resolution modeling of surfaces and 3D shapes.
  • Level-of-detail modeling for analysis and visualization of 3D scalar fields.
  • Hierarchical terrain models for terrain processing and visualization.
  • Algorithms for visibility computation on triangulated terrain models.
  • Feature-based modeling and understanding for product design and manufacturing.
  • Data structures for meshes and simplicial complexes.
  • Shape modeling and visualization based on combinatorial topology.

Current research areas

  • Spatial data analysis and visualization
  • Spatial data structures
  • Topological data analysis (TDA)
  • Topology-based data visualization

Projects

Modular data structures for meshes and simplicial complexes.

Efficient mesh data structures play a fundamental role in a broad range of mesh processing applications, in computer graphics, geometric modeling, scientific visualization, geospatial data science and finite element analysis. Although simple problems can be easily modeled on small low dimensional meshes, phenomena of interest might occur only on much largermeshes and in higher dimensions, as for simplicial complexes describing the shape of high-dimensional point clouds for analysis and understanding. In our research, we have developed a new data model for meshes and simplicial complexes, that we call a Stellar decomposition, which combines the encoding of minimal connectivity information with a clustering mechanism on the vertices and cells of the mesh. Unlike combinatorial data structures, which explicitly encode the connectivity among cells of the complex, this general approach has been shown to support scalability with size and dimension, and efficient processing in a distributed fashion of fundamental connectivity queries. Based on this model, we have developed new efficient representations for tetrahedral meshes endowed with a scalar field for the analysis and visualization of 3D scalar fields, and for arbitrary simplicial complexes. We have also devised a new and highly efficient decimation approach based on a Stellar decomposition, which simplifies large simplicial complexes by their homological properties.

research_modular_data_structures

Modeling and analysis of very large terrains reconstructed from LiDAR point clouds.

Available software tools for terrain reconstruction and analysis from LiDAR (Light Detection and Ranging) data contain a variety of algorithms for processing such data, but most of them require converting the original point cloud into a raster model. This conversion can seriously affect data analysis, resulting in loss of information, or in raster images being too big to be processed on a local machine. Our solution is dealing directly with the scattered point clouds, and thus an unstructured triangle mesh connecting the points needs to be built, encoded and processed for data analysis. Existing tools which support working on triangle meshes generated from LiDAR data can only handle triangle meshes of limited size. The lack of scalable data structures for triangle meshes greatly limited their applicability to very large point clouds currently available, which can vary from 0.2 to 60 billion points. In our research, we have developed a family of new data structures, the Terrain trees, for big triangle meshes, based on the Stellar decomposition model, and we have shown their efficiency and effectiveness for spatial and connectivity queries, and for morphological analysis of very large triangulated terrains on commodity hardware. Our representations use spatial indexes to efficiently generate local application-dependent combinatorial data structures at runtime, and thus are extremely compact and well-suited for distributed computation.

research_terrain_tree_v2

Efficient computation of multi-parameter persistent homology.

Multi-parameter persistent (multi-persistent) homology is an extension of persistent homology, which is a multiscale approach to homological shape analysis, to the case where several scalar functions are associated with the data (multifield data). The objective of our research on multi-persistent homology is to devise algorithms for efficiently computing it on real-world data sets. This is a challenging problem, since very few results exist in the literature on multi-persistent homology, both from a computational and a theoretical point of view. We have proposed a pre-processing approach which computes a Morse-like discrete vector field compatible with the multifield. Such algorithm is well suited to be used with both simplicial complexes and regular grids, it scales well when the size of the input complex increases and is well suited for a parallel implementation. Moreover, we have shown that the use of such pre-processing provides an improvement of at least one order of magnitude in the computation of multi-persistent homology.

research_multi-parameter_persistent_homology_v2

Tree mapping and reconstruction from aerial and terrestrial LiDAR data.

The objective of this research is to develop new approaches for tracking forest characteristics in connection to forest analysis and biomass estimation. Specifically, identifying individual trees composing a forest is crucial for characterizing forest evaluations and forecasting their changes. The emerging LiDAR technology provides an efficient way of performing forest inventory, thanks to the 3D resolution of such data, their high accuracy and cost efficiency over large-scale regions. This project demonstrates how to fully exploit the benefits from topology-based concepts and approaches on forestry LiDAR point clouds to extract individual tree structures automatically. Current techniques for individual tree segmentation require tuning a large number of parameters, and intense user interactions, and they are designed to work only with specific types of forests. The objective of this research is to develop new topology-based techniques for point clouds, both from airborne and terrestrial LiDAR acquisitions, which are general, parameter-free and scalable. By moving from single-time LiDAR point cloud data to multi-date point clouds, which are scanned from the same forest at different times, we plan to investigate the robustness of tree mapping methods to help analyze and segment LiDAR point clouds over-time.

research_treemapping

Topology-based analysis and visualization of multi-fields data.

The use of multifield data (i.e., data characterized by multiple scalar functions) is becoming more and more common in applications. Multifield data are notoriously difficult to analyze and visualize since their analysis combines the challenges of working with two- or three-dimensional domains with those of dealing with a high-dimensional codomain where color maps are ineffective. Thus, the ability to extract features describing the essential properties of such data becomes crucial. The aim of this project is to develop innovative tools for extracting and visualizing topological features describing a multifield. Many aspects of topology-based analysis of multifield data are still unexplored both from a theoretical and practical standpoint. The first challenge addressed in this project is to develop theoretically grounded tools for the analysis of multifield data, based on topology-based descriptors rooted in multi-persistent homology. The second challenge is to evaluate the significance of such tools in the context of applications, and specifically we focus on environmental ones, where we plan to use topological features to segment multifield data for forest monitoring, and to identify regions of non-correlation in time-varying sequences of multifield oceanic data.

Topo-bathymetric data analysis and visualization for coastal ocean modeling.

Bathymetric and shoreline data are often collected at higher resolutions than necessary for coastal modeling, and thus they require a generalization process, where the resolution needs to be optimized based on the tradeoff between representing geometric features relevant to the model processes and computational efficiency. Contemporary coastal ocean models often utilize unstructured mesh representations of coastal regions, which, compared to regular square grids, are more adaptive and allow for better conformity to shoreline and bathymetry. Finer resolution along narrow geometric features, steep gradients, and submerged channels, and coarser resolution in other areas, significantly reduces the size of the mesh while maintaining a comparable accuracy. The objective of this research is to investigate the effects of mesh simplification algorithms on modelled water level observations, with the goal of identifying the simplification approach that best increases performances by reducing mesh elements without significantly affecting model quality. Specifically, we plan to focus on a new scalable topology-aware simplification strategy developed on Terrain trees that preserves relevant bathymetry features, not removing or creating critical points. This research is conducted in collaboration with researchers at NOAA (National Oceanic & Atmospheric Administration).

research_topo-bathymetric

Check NSF project: Geospatial Data Representation and Analysis through the Stellar Decomposition

Software

ICT - Introduction to Computational Topology

The ICT - Introduction to Computational Topology is a web-based user-guide on computational topology equipped with interactive examples to facilitate the comprehension of the notions at the of such theory. Currently the guide presents a description of persistent homology.
The source code and additional information can be found on GitHub.
Moreover, an interactive guide to Persistent Topology can be found on GitHub.

software_ict

Forman Gradient 2D

The Forman Gradient 2D is a comprehensive library for computing a Forman Gradient on triangle meshes.
The library provides all the basic functions for encoding a triangle mesh and a scalar function defined on its vertices (both provided in input) and for computing a Forman gradient on it. Two different methods have been implemented. The first one is based on homotopic expansion and the second one uses an input watershed segmentation to avoid spurious critical simplices. Additional functions are furnished for computing the cells of the discrete Morse complex and for producing output files to be visualized in Paraview.
The library is composed of two main parts. The first one provides all the basic functions for managing the triangle mesh (LibMesh). The second part provides the functions for computing the Forman gradient and the Morse cells (LibForman).
The source code and additional information can be found on GitHub.
References:

  1. Computing a Forman Gradient From a Watershed decomposition
  2. A primal/dual representation for discrete Morse complexes on tetrahedral meshes

software_grad1

Supertetras

The Supertetras is a C++ tool for computing an oversegmentation of a tetrahedral mesh. The tool extends the state-of-the-art superpixel algorithm to tetrahedral mesh representations with scalar fields defined over their vertices.
The source code and additional information can be found on GitHub.
Reference: Supertetras: A Superpixel Analog for Tetrahedral Mesh Oversegmentation

software_supertetras

Superfacets-2D

The Superfacets-2D is a C++ tool for segmenting the boundary of triangulated 3D shapes into patches. The tools computes superfacet segmentations of meshes based on a k-means style approach using shortest-path distances over the face graph of the mesh. By using a bounded expansion strategy in the reclassification step, our approach obtains a log-linear complexity, enabling the segmentation of large meshes (with several million triangles) where applying normalized cuts or other such cut-based approaches would be intractable.
The source code and additional information can be found on GitHub.
Reference: Fast and Scalable Mesh Superfacets

software_superfacets-2d

Mangrove Topological Data Structure (Mangrove TDS) Library

The Mangrove Topological Data Structure (Mangrove TDS) Library is a C++ tool for the fast prototyping of topological data structures representing cell and simplicial complexes of any dimension, not necessarily embedded in an Euclidean space. All types of domains are supported efficiently, including non-manifolds.
The source code and additional information can be found on Sourceforge.
Reference: Representing Simplicial Complexes with Mangroves

TetraMesh

The TetraMesh is a C++ library for the topological representation of scalar fields defined on tetrahedral meshes.
The underlying tetrahedral mesh is encoded as an indexed data structure with explicit adjacencies and the scalar function is associated with its vertices. The library provides all the functionalities for reading a mesh (in TS or RAW format) and for retrieving the topological relations among its simplices such as Vertex-Edge relation, Edge-Face relation, Face-Tetrahedra relation and so on.
The source code and additional information can be found on GitHub.

MT Package

The MT Package contains a C++ library that allows you to design interactive applications which exploit the full power of multiresolution on geometric objects represented by meshes in any dimension.
There are two basic actions in multiresolution modeling:

  1. Take a simplicial (e.g., triangular, tetrahedral) mesh describing an object and build a multiresolution representation of the same object;
  2. Query this multiresolution representation on-line to obtain meshes representing the object at the level of detail you like.
The MT package provides libraries to support both actions. Based on the MT libraries, you can write a program to build a multiresolution representation, as well as a program to query a multiresolution representation. Some demo programs to query a multiresolution representation are provided togther with the MT libraries, while programs to build a multiresolution representation are distributed separately.
The source code and additional information can be found on GitHub.

software_d1view

MT Delaunay

The MT Delaunay is a set of programs dealing with (constrained) Delaunay triangulations of terrain data (triangulation in the plane with elevations associated with vertices). They can be used to build a triangulation with a set of points, to simplify an existing triangulation by removing a subset of the points, and they can also be used to build an MT during this process.
The source code and additional information can be found on GitHub.

software_deccdt