Achraf Bennis

Led the conception and implementation of AI Voice and agentic systems for Forelight's products. Directed associated research and development works, leveraging cloud platforms and advanced AI technologies.

Implemented a comprehensive pipeline for leukemia treatment using Machine Learning, Deep Learning, and Data Science techniques with computer vision. This involved pre-processing multi-resolution microscopic slides, segmenting cells, and classifying cancer types with customized clustering.

Analyzed operator movement from digitized video recordings, transforming time series data for smoothing using mathematical filters like Butterworth and FFT. Implemented a K-means-based clustering method with DTW metric to compare body movement sequences.

Implemented Machine Learning algorithms to automate failure detection in electricity feeders, pre-processing feeder characteristics and failure history data. Developed and compared classical Machine Learning models and Deep Learning approaches for network classification.

Pre-processed claim reports using NLP techniques like stemming, stop word removal, and TF-IDF for text representation. Implemented and validated various Machine Learning models to predict claim fairness, deploying validated models via an R Shiny application.

Pre-processed audio signals and extracted features using Python libraries for automatic speech stress detection. Implemented Machine Learning and Deep Learning models, including CNNs, for accentuation detection, validating models with k-fold cross-validation.

Analyzed and pre-processed bank data using statistical and visualization methods to define use cases like churn rate prediction. Implemented and validated various Machine Learning models for defined tasks using Python's Scikit-learn library.

Implemented a Deep Learning method (MLP) for solving partial differential equations. Utilized the Scikit-learn and Keras libraries for this research project.

Completed a three-year intensive undergraduate course designed to prepare for competitive entrance examinations to French Engineering Schools. This rigorous program focused on foundational subjects essential for advanced engineering studies.

Pursued an engineering degree in Applied Mathematics and Computer Science, with a specialization in Machine Learning. The curriculum covered advanced topics in data science, algorithms, and artificial intelligence.

Obtained a PhD degree focusing on Deep Learning field-agnostic approaches for survival analysis and predictive modelling. Research involved developing novel deep learning methodologies applicable across various domains for time-to-event analysis and forecasting.