Leila De Floriani
Leila De Floriani is a professor at the University of Maryland, College Park. She has been a professor at the University of Genova (Italy) since 1990, 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, Rensselaer Polytechnic Institute, and the Italian National Research Council.
De Floriani is the IEEE Computer Society 2019 President-Elect/ 2020 President. She is a Fellow of IEEE, a Fellow of the International Association for Pattern Recognition (IAPR) as well as a Pioneer of the Solid Modeling Association. She has been a member of the Board of Governors of the IEEE Computer Society (CS) in 2017 and 2018. She is an IEEE Computer Society Golden Core Member. She has been the chair of the 2018 IEEE CS Audit Committee and has served as a vice-chair of the IEEE CS Fellow Nomination Committee in 2017 and 2018.
She bas 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 2004-2008. De Floriani is currently an associate editor of ACM Transactions on Spatial Algorithms and Systems, GeoInformatica, and Graphical Models. She has served on the program committees of over 150 leading international conferences, including several IEEE conferences, and has contributed to many conferences in a leadership capacity.
De Floriani has authored over 300 peer-reviewed scientific publications in data visualization, geospatial 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.
Honors and Awards
IEEE Computer Society, Society of Golden Core
For contributions to geometric modeling and visualization
For contributions to geometric modeling and algorithm design for computer vision applications