I am developing machine learning algorithms to make sense of the data collected by CERN. I have around 10 years of experience in developing complex data analysis software for big data experiment. Always interested in opportunities and collaborations for solving practical problems with real-world impact

My main skills are:
• Convolutional Neural Networks for pattern recognition in images using Keras, Tensorflow, Pytorch
• Graph Neural Networks for point cloud segmentation and regression using Pytorch, Pytorch-Geometric, Tensorflow
• Transformers for classification and regression problems
• Boosted Decision Trees for multivariate classification using XGBoost
• Autoencoders for anomaly detection in data
• Methods for distributed training and hyperparameter optimisation
• Statistical modelling and hypothesis testing, Maximum likelihood estimation
• Visualisation of complex datasets
• Simulation of particle interactions and detector systems using Geant4
• Development of modular and portable software using C++, Python and bash