Loann GIOVANNANGELI

Ph.D. in Computer Science

LaBRI, University of Bordeaux, France

[FR/ENG]

About me.


From 2020 to 2023, I conducted my Ph.D. at the University of Bordeaux (France), under the supervision of Romain BOURQUI ; in close colaboration with Romain GIOT and David AUBER.

``Automatic Evaluation of Abstract Visualizations using Automated Learning Techniques" (in French)

I am member of the BKB team (``Bench to Knowledge and Beyond") of the LaBRI institute. I am also co-organizer of the BKB team meetings, member of the AFoDIB P.h.D. students association committee and member of the LaBRI Laboratory Council as representative of P.h.D. students. I am also involved in the laboratory workshops: ``Psychosocial risks among P.h.D. students" and ``Ecology: Building-Energy-Equipment".

From 1st October 2019 to 31st September 2020, I was Research Engineer in the BKB team of the LaBRI.

I obtained my Master degree in Computer Sciences (Software Engineering) in 2019 at the University of Bordeaux.

Research.


Keywords

Information Visualization, Deep Learning, Graph Visualisation, Automated Evaluation

Interests

My research interests are centered around Information Visualization (VIS) and Artificial Intelligence (AI) (Machine Learning [ML] and Deep Learning [DL]) ; more specifically AI applications for VIS (AI4VIS).

With the outbreak of IoT, the amount and complexity of collected data keeps increasing. This makes their efficient restitution even more important and many visualization techniques that yesterday enabled their exploration are now outdated. Hence, the VIS community keeps on defining new visualizations and guidelines that scale to these complex data.
In this context, the objective of my research is to propose new solutions, based on Deep Learning, to automatically generate and/or evaluate visualizations. For these two tasks, the heterogeneity of modern data makes it difficult to design efficient algorithms/protocols that can be generalized to any datum. On the other hand, DL techniques require large amounts of data to train and become efficient. Leveraging Deep Learning techniques in the context of VIS could enable to explore more exhaustively the parameters space of visualization techniques ; and define automated and reproducible criteria for VIS evaluations.

Leveraging the background of the BKB team of LaBRI, most applications of my AI4VIS researches are dedicated to Graph Visualization.

Supervision

Publications.


Most PDF are accessible on https://hal.science/search/index/q/*/authIdHal_s/loanngio [loanngio]

C : Conference, score taken from Core ranking portal
J : Journal, score taken from Scimago

J Q1 Overlap Removal by Stochastic Gradient Descent with(out) Shape Awareness Loann Giovannangeli, Frederic Lalanne, Romain Giot and Romain Bourqui IEEE Transactions on Visualization and Computer Graphics (TVCG) 2024 Extended version 10.1109/TVCG.2024.3351479
C A Guaranteed Visibility in Scatterplots with Tolerance Loann Giovannangeli, Frederic Lalanne, Romain Giot and Romain Bourqui IEEE Visualization (VIS 2023) Oct 2023 10.1109/TVCG.2023.3326596
J Q1 Toward Efficient Deep Learning for Graph Drawing (DL4GD) Loann Giovannangeli, Frederic Lalanne, David Auber, Romain Giot and Romain Bourqui IEEE Transactions on Visualization and Computer Graphics (TVCG) 2022 Extended version 10.1109/TVCG.2022.3222186
C A FORBID: Fast Overlap Removal By stochastic gradIent Descent for Graph Drawing Loann Giovannangeli, Frederic Lalanne, Romain Giot and Romain Bourqui International Symposium on Graph Drawing and Network Visualization (GD2022) 2022 10.1007/978-3-031-22203-0_6 Best Paper Award (Track 2)
J Q1 Color and Shape efficiency for outlier detection from automated to user evaluation Loann Giovannangeli, Romain Bourqui, Romain Giot and David Auber Visual Informatics 2022 10.1016/j.visinf.2022.03.001
C A Deep Neural Network for DrawiNg Networks, (DNN)² Loann Giovannangeli, Frederic Lalanne, D. Auber, Romain Giot and Romain Bourqui International Symposium on Graph Drawing and Network Visualization (GD2021) Sep, 2021 10.1007/978-3-030-92931-2_27
C B Analysis of Deep Neural Networks Correlations with Human Subjects on a Perception Task Loann Giovannangeli, Romain Giot, D. Auber, Jenny Benois-Pineau and Romain Bourqui International Conference Information Visualisation Jul, 2021 10.1109/IV53921.2021.00029
J Q2 Toward automatic comparison of visualization techniques: Application to graph visualization Loann Giovannangeli, Romain Bourqui, Romain Giot and David Auber Visual Informatics 2020 10.1016/j.visinf.2020.04.002

Teaching.


Master

IUT (Universitary Technical Institute)

Project supervision

Resources.


 [0000-0002-9395-6495]

 [loanngio]

 [Giovannangeli, L]