Machine Learning Applications (Phase 2)

This project focuses on applying Artificial Intelligence algorithms and strategies to automate complex tasks and solve real-world problems by leveraging human pattern recognition capabilities. Multiple areas of social and technological impact are addressed. Socially, the goal is to develop technology to assist visually impaired individuals, particularly in daily activities like card games, given the high prevalence of visual impairment in Ecuador. Furthermore, the computational power of machines is explored to automate the diagnosis of mental disorders, supporting healthcare professionals dealing with extensive symptom taxonomies. In computer vision, facial recognition is investigated for ethnic classification within the Ecuadorian context, where miscegenation creates facial trait similarities. Finally, the integration of AI techniques such as Neural Networks and Fuzzy Logic is proposed to ensure availability and optimize resources in Cloud Computing environments, responding to the exponential migration of applications to server farms and the need for high-performance computing infrastructure.<br/><br/><b>Goal</b>: <br/>Develop Artificial Intelligence strategies for task automation across various fields, addressing issues such as assistance for visually impaired individuals, mental disorder diagnosis, ethnic classification via facial recognition, and resource optimization in Cloud Computing environments.<br/><br/><b>Research lines</b>: <br/>Artificial intelligence and data mining