Graduated cum laude with a master’s degree in Computer Science Engineering for Intelligent Systems at University of Palermo, Italy, presenting a Thesis in Robotics on Design and Implementation of Modules for the Extraction of Biometric Parameters in an Augmented BCI Framework.
Previously graduated with the grade of 110/110 with a degree in Computer Science Engineering, presenting a Thesis in Artificial Intelligence / Latent Semantic Analysis on an Intelligent Interrogation System on official documents of the European Parliament.
Interested in Robotics, Artificial Intelligence, Human-Robot Interaction, Machine Learning, Cognitive Robotics, Image processing, 3D Computer Graphics, Mechatronics, Cybernetics, Bionics, Neuroprosthetics, Mathematics, Physics, Cryptography, Algorithms, Networks, Autonomous Vehicles.
Also interested in academic and industrial research in Japan on Robotics and Artificial Intelligence.
Brief introduction to the Master's Degree Thesis:
- The UniPA BCI Framework is an augmented framework based on the P300 paradigm and allows a user to select individual actions to be performed by a robot or, in the more classic configuration, to spell a sequence of symbols.
- The framework takes advantage of additional developed modules, which perform the acquisition of eye gaze coordinates and biometric signals.
- The use of such modules allows to achieve a combined response which does not only take in account the response of a traditional BCI system based on the P300 paradigm, but it also considers useful information, such as the user visual focus and her level of engagement with the system, providing a more robust and effective global response.
Link to the Project page:
Brief introduction to the Bachelor's Degree Thesis:
- The experimental thesis is about the application of Latent Semantic Analysis (LSA) in automatic and intelligent information retrieval systems of natural human-machine dialogue.
As a result of the thesis, I have developed the software LSA-Bot (Java / Eclipse / Linux) serving as intelligent chat-bot based on the power of Latent Semantic Analysis techniques.
- It is a novel technique for information retrieval that combines the Chatbot-like interaction between user and machine to the intuitive latent semantic analysis techniques applied to a large amount of documents.
- LSA-Bot is a new, powerful kind of Chat-bot focused on Latent Semantic Analysis. Using LSA it is possible to relate words to their vectorial representation, permitting to realize an intelligent chat-bot that can understand human language and can answer to natural language questions as well.
Link to the Project page: