Engineer
Baker Hughes, a GE Company
Total years of experience :7 years, 5 Months
Gas turbine maintenance schedule and cost optimization (Evolutionary based
algorithms).
Parts and stock classification (Keras DNN with word embedding)
Make to Stock/ Make to order classification (Hybrid model was used based on
feature engineering of the stock demands (Confidence interval and number of
hits), then these feature was used to train a neural network model with other
features (e.g. lead time, price, cost, ...)
Stock-demand forecasting and optimal stock level.
with
tensorflow back-end
Traffic forecasting for autonomous vehicles.
Optimal economical route choice based on forecasting knowledge.
FIRENZE, 50127, ITALY
2018
Machine learning and computational intelligence model for traffic forecasting with outliers detection. Implement a possibilistic fuzzy clustering model for detecting unusual traffic patterns (Outliers rejection) hybrid ensemble Neural network for multi-link traffic forecasting. Assistant Lecturer at University of Genoa, Genoa February 2015 – June 2016 Teaching: - Machine Learning - A Computational Intelligence Approach
Machine learning and computational intelligence model for traffic forecasting with outliers detection. Implement a possibilistic fuzzy clustering model for detecting unusual traffic patterns (Outliers rejection) hybrid ensemble Neural network for multi-link traffic forecasting. Assistant Lecturer at University of Genoa, Genoa February 2015 – June 2016 Teaching: - Machine Learning - A Computational Intelligence Approach
Grade A for best project idea attend to lectures in Economy, Communication, Innovation, Valorization, Research Funding, Patent Law, New Methods for Information and Communication, and a Personal Professional Project.
2018 Diploma
Education
courses: Freelance software engineer January 2016 – July 2017 Electricity load forecasting (green energy system). Trajectory clustering (Detecting customer stops and interest in buying products in a market). Deep learning for Email marketing (Churn prediction). One-Shot Learning with Siamese Networks. Image
Regularization Methods for Machine Learning, MIT, IIT 2014 Machine learning and Computational Intellegence, University of Genoa 2014 Neural Networks and Deep Learning, deeplearning.ai, and Stanford University October 2017 Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, deeplearning.ai, and Stanford University October 2017 Structuring Machine Learning Projects, deeplearning.ai, and Stanford University November 2017 Convolutional Neural Networks, deeplearning.ai, and Stanford University November 2017 Management for Scientist and Engineers, SOSMSE 2014 - School of Science Management for Scientist and Engineers July 2014 Big Data analytics, Rulex company 2015 Google Scholar https://scholar.google.it/citations?user=OJitnrMAAAAJ&hl=en Courses PUBLICATIONS