Research Internship focused on the implementation of Deep learning techniques for Natural Language Processing (NLP) and the creation of chatbots.We created a football chatbot with the peculiarity of using a modified version of word-to-vec called char-to-vec, allowing it to identify and correct input typos. It also obtained the data from real-time open-source databases like WikiData using SQL queries.The internship culminated into a paper for the IWSDS-18 conference (International Workshop on Spoken Dialog System Technology 2018) in Singapore.

Multinational consulting company based on SAP. The job position is focused onimplementing Business Intelligence techniques for different clients. My role was to design the database and create meaningful and visually appealing visualizations.

The ESAOTE Group is one of the world´s major manufacturers of ultrasound imaging equipment. ESAOTE Europe B.V. designs develops, manufactures and distributes non-invasive ultrasound imaging equipment. The Advanced Project Group investigates new ultrasound applications and promotes ultrasound research on Universities across Europe.Within this scope, I focused, in the context of ultrasound image classification, on deep learning neural networks for the automatic detection of blood vessels in ultrasound images. My investigations in this promising new field were in relation to 1) train a deep learning neural network, 2) to set up a deep learning computer environment and 3) to analyze the results of the trained network. The dataset for training was based on patient data manually labeled by doctors. For this investigation, the company and I had to learn and understand the new field of deep learning.