In recent years, I have had the privilege of supervising several thesis students, supporting them in developing their theses and providing them with the necessary skills to tackle complex topics. Below, I describe in detail the various research areas in which I have assisted the students and the specific contribution made to each of them.

Research Areas

Recommendation Systems for Social Media

• Description: I supported a student in studying recommendation systems applied to social media using machine learning techniques. We focused on collaborative filtering algorithms, content-based filtering, and the integration of deep learning techniques to enhance personalization and recommendation effectiveness.

Big Data and Health

• Description: With another student, we explored the application of big data in the healthcare sector. This included analyzing large volumes of clinical data, predicting diseases through machine learning models, and implementing data mining techniques to extract useful information from healthcare datasets.

Artificial Intelligence for Sports

• Description: I guided a student in studying artificial intelligence techniques applied to sports. We analyzed how AI can be used to improve athletic performance through monitoring athletes’ biometric data and optimizing training strategies using predictive models.

AI Chatbot

• Description: I assisted a student in developing intelligent chatbots using NLP (Natural Language Processing) and machine learning techniques. The goal was to create chatbots capable of understanding and responding to complex requests, enhancing user-machine interaction.

Phrase Comparison for Similar Structures

• Description: In this project, we worked on comparative analysis of phrases to identify similar structures. This included using NLP techniques for tokenization, grammatical and syntactical analysis, and implementing semantic similarity models.

AI Chatbot for Urban Computing

• Description: I supervised the development of chatbots for urban computing applications, aiming to improve urban management through AI. This involved designing chatbots for traffic management, citizen information, and optimizing urban services.

Amazon Review Analysis

• Description: I assisted a student in analyzing Amazon reviews using sentiment analysis and machine learning techniques to identify trends and patterns in product reviews.

Political Data and Explanation

• Description: In this project, we analyzed political data and developed explanation models to interpret and explain the decisions made by machine learning models applied to political data.

Subjects Taught

Laboratory and Tutor for Fundamentals of Computer Science

As a laboratory tutor for Fundamentals of Computer Science, I guided students through practical exercises, introducing them to programming principles, basic algorithms, data structures, and fundamental computer science concepts.

Computer Networks Instructor

As a computer networks instructor, I assisted students in understanding network protocols, network architectures, network management and configuration, and network security.

Private Tutor for Machine Learning and Deep Learning for Companies

I offered private lessons in machine learning and deep learning for professionals and companies, covering topics such as regression, classification, clustering, neural networks, CNN (Convolutional Neural Networks), RNN (Recurrent Neural Networks), and implementing advanced models using frameworks like TensorFlow and PyTorch.

In all these experiences, I have sought to impart the necessary technical knowledge and a critical and analytical approach, encouraging students to develop innovative and practical solutions to the challenges posed.