Our
Projects
Our research projects integrate cutting-edge digital humanities methodologies, emphasizing the intersection of literature, linguistics, artificial intelligence, and interactive technologies. We explore innovative approaches to textual analysis, narrative creation, and educational applications, aiming to reshape traditional paradigms of humanities study and pedagogy. By employing computational tools, AI models, and immersive media, we foster interdisciplinary collaborations and contribute to advancing knowledge within the field of digital humanities and natural language processing.
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Digital Shakespeare explores how modern technology can enrich Shakespearean scholarship. This project applies digital humanities methods – from AI-driven text analysis to network visualization – to Shakespeare’s plays. By classifying early modern texts and mapping character interactions, it uncovers patterns and relationships not evident through traditional study. The goal is to provide fresh insights into Shakespeare’s works and demonstrate how computational tools can deepen our understanding of literary history.
Language models do not always give answers that match what people expect. This research teaches models to respond in safer and more helpful ways using feedback from people. We also design simple ways to test how well the models are working and make the training process easier.
This research creates AI tools that help doctors and medical staff with tasks like summarizing records or explaining medical information. We train both large and small language models using medical data and expert advice to make sure they are correct and safe. The goal is to support medical professionals and improve patient care.
Education AI helps people learn by giving personalized support based on their level and needs. We use language models to check writing, answer questions, and explain ideas in ways that are easy to understand. The system also learns from students’ responses to give better feedback and keep them interested.
AI-Generated Fiction examines the creative potential of artificial intelligence in storytelling. The project uses AI models to produce narratives, exploring how machines can emulate human-like imagination. By analyzing AI-authored stories, it questions notions of originality and creativity, and asks what it means to be an “author” when a narrative is machine-made. Ultimately, this research sheds light on the evolving relationship between human writers and intelligent algorithms in literature.
AI-Powered VR Narrative Generation combines artificial intelligence with virtual reality to create immersive storytelling experiences. This project is developing a system where AI dynamically generates storylines and characters within a VR environment. The aim is to allow narratives to adapt in real time to user interactions, making each experience unique. By merging AI-driven plot generation with interactive media, the project seeks to transform how we engage with stories in virtual spaces.
AI and Authorship investigates how artificial intelligence is reshaping the concept of authorship. As AI tools like advanced language models contribute to writing, this project explores questions of creative agency and intellectual ownership. It looks at the blending of human and machine contributions in texts, challenging traditional ideas of a single author’s voice. Broadly, the goal is to understand how the rise of AI co-writers influences our definitions of author, originality, and literary value in the digital age.
This research is inspired by how people understand and use language. We study human thinking processes like attention, meaning, and context, and apply those ideas to AI. Our goal is to build systems that understand language more like humans and communicate more clearly.
Open AI Education focuses on integrating AI technologies into teaching and learning in an open and accessible way. This project examines how AI tools (like generative text models) can support students and educators, for example by acting as writing assistants or personalized tutors. It also addresses the challenges of AI in the classroom – from academic integrity to skill development – and proposes strategies for leveraging AI as a positive educational resource. Ultimately, the goal is to develop best practices for using AI to enhance learning, much as calculators once transformed math education.
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