Projects
Our projects page showcases a diverse range of innovative research initiatives aimed at advancing AI, NLP, and intelligent systems. From enhancing search relevance with large language models to developing unbiased ranking systems, each project tackles real-world challenges with cutting-edge technology. Explore efforts in combating AI misinformation, personalizing user experiences through adaptive systems, leveraging graph theory for search optimization, and advancing digital security with AI forensics. These projects reflect our commitment to creating impactful, user-centric solutions that drive progress across various domains.
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Applying graph theory to create personalized search experiences by modeling user preferences and query contexts.
Investigating techniques to attribute AI-generated content, advancing digital security and public safety solutions.
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Integrating large language models for improved query alignment and understanding, enhancing search relevance across diverse applications.
Developing dynamic systems that interpret, organize, and present data aligned with user intent for personalized user experiences.
Using meta-learning and novel social prompting to detect and mitigate AI-generated misinformation and hallucinations.
Exploring frameworks to eliminate biases in information retrieval and recommender systems for more equitable outcomes.