Biography

Dr. Madiha Hameed Awan is a PhD-qualified data scientist and AI researcher. She completed her PhD in Computer Science at the Pakistan Institute of Engineering and Applied Sciences (PIEAS) from January 2019 to September 2025 (CGPA 3.28/4). Her thesis is Detection of Cancerous Diseases Using Advanced Deep Learning Approaches. She holds an MS in Computer Science from the University of Lahore (2014–2017) and a BS in Information Technology from the Virtual University of Pakistan (2003–2007).

Her research centres on deep learning, transformer-based architectures, vision-language models, and natural language processing, with applications in medical imaging, proteomics, cancer detection, and clinical decision-support systems. She designs end-to-end AI pipelines spanning supervised and unsupervised learning, model optimization, interpretability, and deployment. Published work includes CCNN-SCD for skin cancer detection, ARiViT for noisy brain medical image classification, ReLViT with YOLO for acute myeloid leukemia on bone marrow images, a systematic review of ISIC skin-cancer methods, and a mini-review of explainable AI for breast ultrasound.

She has served at the University of Gujrat since October 2008. Roles include Teaching Assistant and Department Coordinator (2008–2010), Research Officer (2010–2011), Associate Lecturer (2011–2013), Team Lead, Development for the university LMS (2013–2014), and Administrator (2014–present), covering admissions systems, campus networks, cloud/data-centre transformation, and learning platforms. She was Visiting Lecturer at Arid University, Rawalpindi (2019–2023), teaching Data Science, Machine Learning, and Big Data Analytics, and Data Analyst Trainer (online) at the International Certificate Center, Accra (November 2023–February 2024).

She teaches Data Science, Artificial Intelligence, and Business Analytics, with a focus on outcome-based education and student-centred practice. In 2025 she supervised research on AI-driven breast cancer imaging, explainable AI for multimodal breast diagnosis, and deep learning for thyroid carcinoma. Professional service includes Course Coordinator in the Department of Computing (2011–2013), reviewer for IBCAST (2025), and session chair at the 3rd International Conference on Emerging Trends & Innovation (ICETI).