We are dedicated to advancing knowledge through multidisciplinary approaches, integrating fields such as Human-Computer Interaction (HCI), approximate computing, and embedded systems. Explore our primary research areas below.
We evaluate the use of off-the-shelf Large Language Models (LLMs) like GPT to assess their impact on learning outcomes within educational Virtual Reality (VR) settings. Our studies focus on enhancing immersive educational experiences through intelligent, responsive systems.
This project explores the integration of LLMs to manage Non-Player Characters (NPCs) in gaming environments. By leveraging advanced language models, we aim to create more dynamic and realistic interactions, enhancing player engagement and experience.
In partnership with the Psychology Department, we are developing VR-based exposure therapy programs augmented with AI-driven agents. This interdisciplinary project seeks to improve therapeutic outcomes by providing adaptive and personalized treatment environments.
We investigate the deployment of Large Language Models and neural networks on embedded systems using approximate computing techniques. This research aims to optimize performance and energy efficiency without compromising model accuracy, enabling advanced AI capabilities in resource-constrained environments.
Our work in this area focuses on assessing the fairness of AI models applied to medical datasets, such as dermatology images. We examine model performance across diverse demographic groups to ensure equitable healthcare outcomes and mitigate biases in AI-driven medical diagnostics.
For more information about our projects or to get involved, please contact Dr. Spantidi.