Linda Aouchiche Hadded

As part of Exail’s R&D team, I contributed to the development of a toolbox dedicated to quality control (QA/QC) of sonar data. The goal was to ensure the reliability and traceability of acoustic data collected during offshore operations. Key responsibilities: Designed and developed Python-based user interfaces (UI) for sonar data analysis and visualization. Implemented quality indicators and anomaly detection algorithms for acoustic time-series data. Built a modular toolbox to integrate seamlessly with existing data processing pipelines. Worked in collaboration with field teams and domain experts to tailor tools to operational needs. This experience strengthened my skills in acoustic signal processing, scientific software development, and the integration of QA/QC tools in demanding real-world environments.

At Terradona, I contributed to the development of smart waste management solutions by applying advanced signal processing and AI techniques to lidar sensor data. Working in a multidisciplinary R&D team, I was involved in the entire pipeline — from sensor data acquisition to AI model deployment. Key contributions: Designed and implemented data preprocessing algorithms for lidar point clouds to enable accurate object classification. Developed and trained machine learning models for real-time waste identification and sorting. Built user-friendly interfaces (UI) and toolboxes in Python to visualize and validate system outputs. integrated AI models on microcontrollers and edge devices for autonomous operation. This role strengthened my ability to bridge the gap between raw sensor data and actionable intelligence, with a focus on embedded AI and environmental impact.

teaching assistant statistics and data science

Worked on the development of advanced signal processing algorithms for airborne radar systems dedicated to maritime surveillance, with a focus on detecting moving targets in cluttered sea environments. The work aimed to enhance detection performance in challenging operational conditions involving Doppler and range ambiguities. Key contributions: Defined and specified an emission/reception strategy adapted to the radar’s operational constraints. Developed algorithms to resolve range and Doppler ambiguities, particularly for radars operating with complex PRF schemes. Designed robust detection techniques to handle strong sea clutter and ensure reliable target extraction.

Research and development work in the field of signal processing applied to air surveillance radar systems. The objective of the PhD was to design new high-resolution detection and localization methods for small, slow-moving targets, often masked by clutter or affected by range/Doppler ambiguities. Key contributions: Developed a new radar signal processing chain adapted to ambiguous radars, integrating advanced techniques for resolving range-Doppler ambiguities. Designed adaptive detection algorithms based on robust estimators of noise and clutter covariance matrices. Implemented high-resolution techniques for the joint estimation of range and Doppler velocity. Validated performance using both simulated and real-world datasets, in collaboration with Thales Air Systems.

Practical work - Electronic oscillators - Amplitude and frequency modulation

Worked on the design and development of an Inertial Measurement Unit (IMU) for estimating the 3D trajectories of aggregates inside a rotating cement mixer. The project aimed to improve material flow analysis in industrial processes using embedded sensing and signal processing. Key contributions : Integrated and calibrated inertial sensors (accelerometers and gyroscopes) for robust motion tracking in a constrained environment. Applied Multidimensional Scaling (MDS) techniques to reconstruct spatial trajectories from noisy sensor data. Developed and implemented a Kalman filter to fuse sensor measurements and enhance trajectory estimation accuracy. Analyzed sensor behavior under strong non-linear dynamics and rotational disturbances. This experience provided valuable hands-on exposure to sensor fusion, inertial navigation, and real-world industrial applications of signal processing.