I’m a qualified and results-driven doctoral researcher and data scientist, currently pursuing a PhD focused on deep learning and medical imaging for diabetic retinopathy classification.

Throughout my career, I have built solid experience across research, consulting, and industry roles, including:

• Lead Data Scientist at DNA Global Analytic (Geneva

• Project Lead at iConnectServices (Tunis)
  
  

I have applied data science in domains working with very large and complex datasets, such as biology, physics, and social sciences, and have hands-on experience with sensor data standards and sensor systems.

With over  years and yers of practical experience, my expertise spans:

Supervised & unsupervised learning
Classification models & cluster analysis
Neural networks & non-parametric methods
Multivariate statistics, reliability models, Markov and stochastic models
Bayesian models and document evaluation for NLP corpora

📌 Engineering & algorithm development:

Image processing: segmentation, filter design, noise reduction, compression, image fusion, super-resolution
Computer vision: target acquisition, tracking, optical flow, Kalman filtering, pose estimation
Computational imaging: compressive sensing, synthetic aperture radar (SAR), Doppler beam sharpening
Deep learning: classification, detection, siamese networks, residual learning, deep embeddings, recurrent networks
Machine learning for classification & regression: support vector machines, probabilistic models, neural networks
Domain-specific signal processing: multi/hyper-spectral, RF, IR, SAR

🔧 Technical skills & tools:

Python (including PyTorch, TensorFlow, OpenCV)
MATLAB, Simulink, Stateflow
Model-Based Design
Agile software development methodologies

My work combines deep technical knowledge with a strong focus on delivering analytics-driven solutions that address real-world problems in healthcare, industry, and beyond.