Graduate Program - Quantitative Developer for the Global Market Platform, with a focus on structured products in the secondary market. Developing micro-services with F# to enhance the global modelling framework for trading and structuring teams.

Graduate Program - Product Manager for the Wealth Management Platform, Working in a highly collaborative and agile environment, standing between trading, sales, and IT to automate the OTC derivatives trading platform. Involved in the integration of the Commodity Asian Options, as well as the Interest Rate Swaps.

Master Thesis ”Bayesian Learning for RNA Synthetic Biology,” which aims to forecast prokaryotic ribo-regulators translation initiation rates using deep learning-based approach, including graph neural networks, convolutional neural networks, multi-layer perceptron, and long short-term memory models. Demonstration of the positive correlation between RNA nucleotides long-range interactions and RNA functionality.

Deep learning engineer in a cross-functional entity of TotalEnergies for layout analysis and metadata extraction. Development of object detection and object recognition models using the PyTorch framework. Training of the FasterRCNN and the Yolov5 architectures using the Pangea III supercomputer (HPC) (using LINUX). From research prototyping to production deployment.

Member of the Core Platform team to support the trading desk developing dashboarding applications. AI-based approach for anomaly and fraud detection: machine learning-based method, use of scikit-learn, pandas, numpy, os, openpyxl. Unsupervised learning using the isolation forest algorithm on sparse data.

Towards Lifelong Domain Adaptation for Face Anti-Spoofing - Deep Learning - Convolutional Neural Networks - Classification