✓ Intelligent Document Processing. ✓ Designed, developed and deployed a separation Head for intelligent document separation, resulting in a full automatisation of the process for the a bank company. -Language models Lilt -Topic Modeling, Latent Dirichlet Allocation ✓ Designed, improved and deployed graph neural network models for intelligent document processing serving top tier manufacturing and banking companies. ✓ Deployment and serving through GCP. ✓ HuggingFace, PyTorch, Docker, Cloud functions, Flask, REST, Git, clickup, analytics, reporting, tableau,

✓ Performing research and development at the forefront in machine learning and deep learning to find algorithms, improvements and optimizations of the performance of predictive models on issues related to time series, vision, regression, classification and to the automl. ✓ Development, deployment and maintenance of prevision.io Auto-ML platform serving +100k monthly users ✓ Designed and developed a meta learning model for accelerating hyper parameter tuning of prevision.io auto ML platform -Bayesian search, TPE, PCA -Constraint Programming, Java, Choco Solver -Meta-learning, Few-shot learning, cold/hot start training ✓ Designed a time series forecasting model for an energy company that improved by 25% their daily energy consumption forecast. -Attention mechanism, Heat-map, Auto-lag values -Keras, Transformers model, LSTM

Creation and implementation of an analysis and learning system for prediction of deviant behavior in virtualized data centers. - Modeled historical workloads using global time series constraints and associated to a - predictive LSTM model.

Develop and implement traversing algorithms for multi-valued decision trees, while taking into consideration aggregation constraints over different valuation type. Problem of product configuration, with application in agriculture.