Signals & Artificial Intelligence (SIA)

Understand, model and ensure the reliability of intelligent, communicating systems.

IPSA’s Signals & Artificial Intelligence (SIA) research team focuses on signals, telecommunications and their many applications in complex embedded systems.

At the crossroads of statistical signal processing, artificial intelligence and robotics, it develops innovative methods for modeling, diagnosing and optimizing critical systems in the aeronautics, space, automotive and healthcare sectors.

THE GOALS

Improve the accuracy of positioning and navigation systems

Automate on-board network diagnostics

Optimizing energy transfer in constrained environments

Apply AI to data from a wide range of fields, from satellites to plants to nuclear gas pedals, to help develop reliable, high-performance, intelligent technologies.

image of satellite antennas pointed at a night sky

Research areas

Statistical signal processing and digital communications

GNSS systems and hybrid navigation

Machine and deep learning (supervised, unsupervised)

Intelligent diagnostics for wired networks (automotive, aeronautics)

Inductive energy transfer and EMC modeling of HV cables

Robust statistical methods on non-Euclidean spaces (Lie groups, Riemannian varieties)

Identification of hybrid systems (continuous and discrete dynamics)

Thematic
research

Navigation and geolocation PVT positioning via GNSS, GNSS/IMU hybridization, RTK, interference robustness, intelligent tracking loop

Energy transfer Optimization of contactless systems for aeronautical applications, electromagnetic behavior of HV cables

Wired network diagnostics Detecting, locating and characterizing faults in embedded systems

Robust & non-Euclidean statistics Bayesian estimation and error bounds on non-Euclidean spaces

AI and deep learning Deforestation detection, sap transport analysis, cross-section prediction in nuclear physics

Health and microwave imaging WaveCare project with Sogeti Labs – non-invasive breast cancer detection using AI and microwaves

Internal
team

Omar AL HAMMAL Enseignant-Chercheur

Leïla GHARSALLI Enseignante-Chercheuse

Data and Decision Science

Abdelhak GOUDJIL Enseignant-Chercheur

Automatic

Samy LABSIR Enseignant-Chercheur

Signal and Telecommunications, Associate Researcher at TéSA

Lorenzo ORTEGA Enseignant-Chercheur

Signal and Telecommunications, Associate Researcher at TéSA

Mostafa-Kamel SMAIL Enseignant-Chercheur

Electronics and Electromagnetism, Head of Signals & Systems Department, Research Associate at GeePs

Serigne DAOUDA PENE : chercheuse post doctorante -

Serigne DAOUDA PENE chercheur post doctorant

“Lie group regression methods for image denoising and registration”.

Imad BOUHOU Doctorante

“Non-stationary and robust Reinforcement Learning methodologies for surveillance applications” (2022-2025)

mohammed terrah phd enseignant chercheur ipsa

Mohammed TERRRAH Doctorant

“Design and optimization of a contactless energy transfer system for aeronautical applications” (2022-2025)

joan bernabeu phd enseignant chercheur IPSA

Joan Miguel BERNABEU FRIAS Doctorant

“Use of phase measurement for precise positioning in a swarm of satellites”; thesis co-financed with CNES and co-supervised at TéSA (2022-2025).

Léa DUBREIL Promo IPSA 2022

PhD student – “AI processing of degraded GNSS measurements as input to a hybridized positioning algorithm (GNSS-IA)”; thesis co-financed with Thales Allenia Space and co-supervised at TéSA (2023-…)

Team co-supervised with
partner laboratories

Esteban MORALES-AGUIRRE

“Generation of precise and robust observables by GNSS/IMU hybridization”; thesis co-financed by CNES and ISAE Supaéro and co-supervised at TéSA (2023-…)

Alexandre BROCHARD

“Detection and Mitigation of Interferences for Satellite Systems”; thesis funded by the FONISEN research federation (ONERA, ENAC, ISAE SUPAERO) and co-supervised with ENAC and ISAE Supaéro (2024-…)

Robin DUPRAT

“Design and Processing of GNSS Meta-Signals for Precise Positioning”; thesis co-financed by CNES and Thales Allenia Space at TéSA (2024-…)

Daniel JIMENEZ

“EMC study and modeling for cable pre-sizing in the automotive industry”; CIFRE thesis co-supervised with ACOME at GeePs (2025-…)

Laboratories and strategic partners

Publications
recent

“Robust Reinforcement Learning for Autonomous Navigation in Complex Environments”, Journal of Artificial Intelligence, 2025.
This study explores the application of robust reinforcement learning in dynamic environments for autonomous systems such as drones, with implications for aeronautics and automobiles.

“Hybrid GNSS/IMU Systems for Precise Satellite Positioning” – Collaboration with CNES and Thales Alenia Space.

The team is developing new methodologies to improve the accuracy of satellite geolocation using hybrid GNSS/IMU systems.