Meet the Research Team

She has secured nearly $1 million in scholarships and research grants. Beyond academia, she is a Certified Fraud Examiner and an active volunteer, serving as Vice President of Karina Association, Inc. El Mahdy is also a public speaker on issues related to higher education, accounting, and finance.

She studies how economic statistics like GDP would change if new measurement methodologies were implemented. Her recent empirical work includes estimates of how measured wealth would change if more items were tracked as consumer durables, how measured GDP would change if data and marketing were tracked as intangible capital assets, and how measured capital transfers would change if radio spectra allocations were tracked. She has also studied the theoretical impact of tracking environmental assets and corporate social responsibility.

His interdisciplinary research bridges AI, data analytics, and human-computer interaction to push the boundaries of intelligent, adaptive systems. His work explores how AI-driven models and data-informed systems can enhance user experiences in virtual and augmented reality environments. Recent projects include leveraging large language models for context-aware content generation, real-time optimization using machine learning techniques, and applying data-driven approaches to improve system responsiveness and user interaction.

His research focuses on artificial intelligence, natural language processing, and human-computer interaction. His work explores the intersection of AI and immersive technologies such as augmented and virtual reality, with applications ranging from 3D content generation to intelligent systems for disaster response. His research integrates vision-language models, optimization techniques, and machine learning to enhance user experience and system adaptability in dynamic environments. His recent projects reflect a strong interest in context-aware computing and the development of trustworthy, multilingual AI systems.

His research focuses on immersive analytics, human-computer interaction, data visualization, and artificial intelligence. His work explores the use of extended reality technologies, including virtual and augmented reality, to support the analysis and visualization of complex data. He is particularly interested in how AI-driven methods, eye-tracking, and cognitive load analysis can improve user understanding and interaction in immersive environments. His recent projects examine the integration of large language models, structured data extraction, and XR-based visualization for domains such as financial analysis, cybersecurity, and corporate social responsibility.

His research is centered on human-AI interaction. His work is characterized by the design and evaluation of AI-driven systems that are informed by physiological and contextual data gathered in real-world environments. Machine learning and deep learning models have been developed by him to infer users’ states from these data streams, and these models have been integrated into large language model agents to support personalized interactions. To evaluate the usability and effectiveness of these AI-driven solutions, user studies have been conducted with domain experts and graduate students. His research contributions have resulted in several peer-reviewed publications across journals, conferences, and workshops.