I am Luis, a 25 year old computer science graduate from Salamanca, Spain. I do things related to Frontend and Backend development and my interests include Data Science, specifically those related to Natural Language Processing (NLP) 🧠 and Natural Language Understanding (NLU) 🤖.

• 📚 Education in Computer Science degree and Computer Science master's degree at the University of Salamanca. Also, Master Degree in Cibersecurity at the University Carlos III of Madrid.
• 💼 Working as a researcher in multiple areas of the IT part, also as a fullstack developer and team leader/manager at BISITE Research Group.
• 🌱 Currently deepening my knowledge in data science and cibersecurity.
• 🛠️ My usual partners when I work are usually:

This is my technology stack badges, including different technologies, programming languages and resources i manage and use from day to day.

• 🌐 OS:
• 🎨 Frontend and design tools:
• 💻 Backend and others:
• 🛢Databases:
• ☁️ Cloud:
• ⚙️ DevOps:
• ⌨️ Systems:
• 🔧Miscelaneous Tools:
• 🧠 Artificial Intelligence:

• Imployed: This is my final degree project, consisting on a series of subsystems (data ingest, storage, NLP processing, chatbot NLU model and web development) forming the architecture to create a platform capable of recommending job offers and online courses based on the knowledge, skills and preferences of the user through an interactional conversation with a chatbot.This application was built following the MERN stack, along with other technologies like Python, Celery, Redis, ETL structure and Rasa (an open-source technology used to create a NLU chatbot model from scratch), among others.

• Twico: This is is the final project for one of the subjects in the computer science master's degree consisting on a set of subsystems to aggregate information from newsitems, Twitter and OpenData sources, for the creation of a dashboard to serve a summary of the COVID pandemic, using different technologies. Take a look!

• coreIA: This is my final computer science master´s degree project, consisting on a series of subsystems (storage, NLP processing, virtual environments, task management and web development) that make up the architecture to create a platform in which, through a web application, it is possible to visualize, download, store and deploy machine learning models (Machine Learning) abstracting the peculiarities of libraries available in the world of artificial intelligence and data science (Tensorflow, Pytorch, SpaCy, scikit-learn, ...). This application was built following the MEVN stack, together with other technologies such as Python, Vue, Scikit-learn, spaCy, among others.

• Fake News Detector: This is my final cibersecurity master´s degree project, consisting on a study that examines whether categorizing news stories as true or fraudulent automatically using cutting- edge artificial intelligence algorithms is beneficial. To approach this investigation, the problem of false news identification was approached by utilizing methods that involve artificial intelligence and natural language processing like Feature Engineering, Machine Learning, Recurrent Neural Networks (LSTM), Ensemble Learning, Convolutional Neural Networks (CNN), and Transformer-based models like BERT. This study analyzes the effectiveness, benefits, and drawbacks of each approach, offering knowledge that might guide the creation of trustworthy tools for spotting false information and confirming the accuracy of data in an interconnected world. Take a look!