I am a PhD student in Bioinformatics at the University of Manchester, funded by the UK Medical Research Council (MRC). My research focuses on developing deep learning methods to infer spatially localized pathway expression from histopathology images using spatial transcriptomics data. More broadly, I am interested in developing machine learning approaches for integrating single-cell and spatial multi-omics data to analyze human tissues in disease and developmental microenvironments. My work lies at the intersection of AI and biomedical data science, with particular expertise in genomics, spatial transcriptomics, and computational pathology. I am also proficient in multiple programming languages and computational frameworks for large-scale biomedical data analysis.

I hold an MSc degree in Computer Science from Information Technology University (ITU), Pakistan. During and after my master’s studies, I worked in several areas including computer vision, natural language processing (NLP), deep learning, and blockchain technologies. My research contributions include algorithms for label-efficient diabetic retinopathy classification using active learning and COVID-19 diagnosis through multi-modal collaborative federated learning, published in IEEE and Springer journals in biomedical imaging and computational science.

Previously, I worked as a Research Associate and Team Lead at the Blockchain Lab at ITU, developing blockchain-based applications for decentralized data storage and machine learning methods to detect illegal activities on the Ethereum blockchain. I also served as a Project Manager at Axcelerate AI, Pakistan, where I developed computer vision software for virtual try-on applications and NLP-based information retrieval systems for multi-source textual data. In addition, I explored deep learning approaches for Urdu poetry generation. In the future, I aim to develop AI-driven healthcare solutions to improve medical services in developing countries through scientific innovation and community-driven initiatives.