I 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.
Besides Artificial Intelligence, Machine Learning and Robotics, I am also interested in Human-Robot Interaction, Cognitive Robotics, Image processing, 3D Computer Graphics, Mechatronics, Cybernetics, Bionics, Neuroprosthetics, Mathematics, Physics, Cryptography, Algorithms, Networks, Autonomous Vehicles. During the course of the academic studies I have learned to program in different programming languages, including C, C++, Java, Python, LISP, Matlab. Past experiences also on Basic, QuickBasic, VisualBasic and specific languages such as SQL, Gams, Prolog, S-Golog, UML, XML, AIML, Assembly.
I am interested in learning about Japan, the Japanese language, culture, lifestyle and job opportunities. I am especially interested in doing academic and industrial research in Japan, mainly on Artificial Intelligence and Robotics.
Resume available at https://goo.gl/fhVEMC
I am interested in growing professionally in the areas of AI related to ML/DL, and Robotics. More in general, I have always been interested in the interaction between humans and machines, whether that would be interacting with a software or a physical robotic agent, IoT or environment sensing, self driving cars, or medical domain, with the desired objective of general AI for a smarter society of the future. I like to do research, learn, experiment and work on innovative concepts and solutions.
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.
DicomReader is a simple Java DICOM files reader and it has been developed as part of the Volumetric Bias Correction paperwork. DicomReader handles headers as well as images contained in the Dicom files: Data (headers and pixel-value images) is saved into ascii plain text files; A pgm version of the image files is provided as an option for the user.
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.