Artificial Intelligence

My Artificial Intelligence (AI) research focuses on ethical and transparent solutions that enhance user trust. I have explored Machine Learning (ML) models for real-world applications, notably in healthcare, addressing critical challenges like data scarcity and decision-making transparency. My work with Generative Adversarial Networks (GANs) has pioneered methods for improving synthetic biomedical data generation, mitigating issues such as mode collapse through adaptive input normalisation.

My efforts in Explainable Artificial Intelligence (XAI) have also introduced interpretable frameworks to ensure end-users can trust AI outputs. These advancements bridge the gap between complex AI models and their real-world utility, fostering societal acceptance and ethical AI deployment.