Open to opportunities

Yasmine CHAIBEN

@yasminechaiben

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Artificial Intelligence engineer specializing in machine learning, computer vision, and GNSS solutions.

France

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What I'm looking for

I seek roles applying ML and computer vision to safety-critical positioning or robotics, with opportunities for research impact and real-world deployment.

I am an Artificial Intelligence Engineer with hands-on experience in machine learning, deep learning, and computer vision, applied to safety-critical positioning and navigation systems.

I have designed and implemented deep convolutional models (ResNet, VGG) and CUDA-accelerated image-processing pipelines, and built predictive models for both GNSS error estimation and time-series forecasting.

My work includes developing adaptive positioning solutions for the Pods4Rail project, characterizing GNSS interference with a 10,000+ sample dataset, and integrating embedded systems for assistive robotics and mobile alerting.

I publish research on GNSS interference management and adaptive navigation for railway applications, and I bring a practical, research-driven approach to delivering robust, real-time perception and positioning solutions.

Experience

Work history, roles, and key accomplishments

Current

AI Research Engineer

Current

Cosys-Leost

Feb 2025 - Present (8 months)

Supported the Pods4Rail project by developing adaptive GNSS positioning solutions and ML models, improving localization precision and enabling effective interference mitigation strategies.

Machine Learning Computer Vision Python PyTorch TensorFlow Deep Learning Data Analysis

AI & GNSS Engineering Intern

Cosys-Leost

May 2024 - Oct 2024 (5 months)

Implemented deep CNNs (ResNet, VGG) for GNSS interference classification on a 10,000+ sample dataset and developed predictive models for positioning error estimation to enhance robustness.

Python Deep Learning Convolutional Neural Networks Data Processing PyTorch TensorFlow Model Evaluation

Engineering Intern

D-WEE Healthcare

Jun 2023 - Aug 2023 (2 months)

Designed and programmed a wheelchair automation kit integrating embedded systems and sensor data processing, and developed an Android app for real-time driver alerts.

Embedded Systems Android Development Sensor Integration Python C C++System Integration Mobile Apps

Initiation Intern

Tunital

Aug 2022 - Aug 2022 (0 months)

Implemented CUDA libraries to accelerate image recognition/classification on NVIDIA GTX1650, achieving roughly 3× faster computation for GPU-accelerated image processing.

CUDA GPU Acceleration Computer Vision Deep Learning Python Optimization

Education

Degrees, certifications, and relevant coursework

National Engineering School of Sousse (ENISo)

Bachelor's Degree in Industrial Electronics, Artificial Intelligence / Industrial Electronics

2021 - 2024

Activities and societies: Final year project (AI & GNSS), internships at COSYS-LEOST and D-WEE HealthCare, research publications in GNSS interference and adaptive navigation

Completed an Artificial Intelligence Engineer program with strong academic training and hands-on projects in machine learning, computer vision, and GNSS-related positioning systems.