I am a dedicated Postgraduate Researcher and a PhD Candidate specialising in AI for Medical Diagnosis and Care at the University of Leeds. My work is at the forefront of integrating artificial intelligence with healthcare, leveraging domain-adaptable deep neural networks for automated analysis of colorectal cancer tumour microenvironments. My research aims to innovate new methods for assessing and adapting computer vision models across heterogeneous histopathology images and clinical data. This includes quantifying novel biomarkers and elucidating their relationship with patient survival rates, paving the way for tailored treatment regimens.I have 5+ years of experience in data science, machine learning, deep learning, computer vision, and programming underpins my academic journey. I possess proficiency in various tools and frameworks essential to the field, including Python, C++, TensorFlow, PyTorch, and OpenCV. Beyond my primary research, I have contributed to population forecasting, employing dynamic microsimulation models to generate synthetic population data.My passion for applying AI technologies in medical diagnosis and care is driven by a commitment to advance healthcare outcomes. As I continue exploring AI's potential in revolutionizing the healthcare industry, I am eager to collaborate with like-minded professionals and organisations at the intersection of technology and healthcare. My goal is to contribute meaningful innovations that enhance patient care and treatment effectiveness through the power of AI.