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Dr. Giulia De Masi

Dr. Giulia De Masi

Dr. Giulia De Masi

Associate Professor, Department of Sciences and Engineering, Sorbonne University Abu Dhabi

PhD Credentials

PhD in Statistical Physics of Complex Networks

Bio

Dr. Giulia De Masi is an Associate Professor, Department of Sciences and Engineering of Sorbonne University Abu Dhabi, and Principal Investigator at Sorbonne Center for Artificial Intelligence (SCAI).

She brings over 20 years of expertise in AI, Machine Learning, and Computational Modeling from both Academia and Industry, with numerous applications to Economics and Engineering.

After her PhD on Complex Networks, she was Post-doctoral Researcher in the Polytechnic University of Marche and Visiting Researcher at Hitachi Research Laboratory, in Nara, Japan. 

Starting In 2008, Dr. Giulia worked for 8 years as a Scientist in the R&D field, where she led Industrial Research projects on AI and Machine Learning applied to Ocean environment.

In 2016 she moved to UAE, where she has been Principal Scientist in applied research Institutions, and Faculty in multiple Academic Institutions. 

Her scientific contributions have been published through numerous articles in leading peer-reviewed journals, presentations at major international conferences, media outreach, patents and reports for the Industry.

She is IEEE Senior member and Associate Editor for ‘IEEE Robotics and Automation Letters’ and for ‘IEEE Journal of Oceanic Engineering’. Additionally, she has been program, workshop and tutorial chair for multiple IEEE conferences.

She has been recognized for her scientific contributions and scholarship by international awards like ‘UAE ambassador for Women in Data Science’ (by Stanford University, 2018), ‘Women in Engineering (WIE) Propel laureate’ by IEEE Oceanic Engineering Society in liaison with WIE (2022), and IEEE Honor member (2024).

She leads multidisciplinary projects with an extensive global network of collaborators, blending AI, Collective AI, Multi-Robot Systems, Sustainability, Energy Efficient Neuromorphic and Bio-Inspired Solutions.

1. Processing Continuous-Valued Signals for Multimodal Spike-Based Pose Regression, Vidya Sudevan, Fakhreddine Zayer, Sajid Javed, Hamad Karki, Giulia De Masi, Jorge Dias, SIMPAR 2025

2. LSTM-enhanced Predictive Display for Time Delay Mitigation in Wireless Underwater Teleoperation, M. ElMezain, S. Iacoponi, F. Zayer, I. Hussein, F. Renda, G. De Masi, J. Dias, OCEANS 2025

3. UW-SwarmSim: a simulator for underwater swarms of robots, S. Iacoponi, A. Infanti, M. Hanbaly, G. De Masi, F. Renda, OCEANS 2025

4. “Underwater Robotic Swarms: achievements, challenges and perspectives”, International Conference on Complex Systems 2025, CCS2025

5. Underwater Human-Robot and Human-Swarm Interaction: A Review and Perspective, Sara Aldhaheri, Federico Renda, Giulia De Masi, OCEANS 2024 - Singapore, Singapore, Singapore, 2024, pp. 1-9

6. Towards Efficient Underwater Robotic Swarms: Edge-Based Comparative Analysis of Multi-Object Trackers, Rim Eltobgui, Fakhreddine Zayer, Saverio Iacoponi, Giulia De Masi, Federico Renda, Jorge Dias, OCEANS 2024 - Singapore, Singapore, Singapore, 2024, pp. 1-7

7. Evaluating Visual-Selective Visual-Inertial Odometry: An End-to-End Multi-Modal Pose Estimation Framework for Underwater Environments, Vidya Sudevan, Fakhreddine Zayer, Sajid Javed, Hamad Karki, Giulia De Masi, Jorge Dias, 2023 21st International Conference on Advanced Robotics (ICAR), 639-644   

8. Comparative Analysis of State-Of-The Art Multi-Object Trackers for Tracking of Underwater Swarms Using Edge Device, Rim Eltobgui, Fakhreddine Zayer, Saverio Iacoponi, Giulia De Masi, Federico Renda, Jorge Dias, ICAR2023  

9. Neuromorphic Fish Species Classification: Bridging Biological and Artificial Intelligence for Sustainable Marine Conservation, Vidya Sudevan, Rizwana Kausar, Fakhreddine Zayer, Sajid Javed, Hamad Karki, Giulia De Masi, Jorge Dias, ICAR2023 

10. Wireless teleoperation of HSURF artificial fish in complex paths, S. Iacoponi, S. Alhajeri, M. Hanbaly, F. Renda, C. Stefanini, G. De Masi, OCEANS 2023 - Limerick, Ireland, 2023, pp. 1-5.

11. Heterogeneous Underwater Swarm of Robotic Fish: Behaviour and Applications, S. Iacoponi, M. Hanbaly, A. Infanti, B. Andonovski, N. Mankovskii, I. Zhilin, F. Renda, C. Stefanini, G. De Masi, Embodied Intelligence Conference 2022, IOP Conference Series: Materials Science and Engineering 1292 (1), 012008, IoP Press , 2023 

12. H-SURF: Heterogeneous Swarm of Underwater Robotic Fish, Saverio Iacoponi, Godfried Jansenvanvuuren, Gaspare Santaera, Nikita Mankovskii, Igor Zhilin, Federico Renda, Cesare Stefanini, Giulia De Masi, Proceedings OCEANS2022 Hampton Roads, IEEExplore

AI, collective AI, multi-robot systems, energy efficient neuromorphic and bio-inspired solutions. 

Data Science. 

Computational Modeling. 

Applications for Ocean Science, Marine Robotics and Sustainability

Researches for Dr. Giulia De Masi

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