Dr. Syed Hamad Shirazi

Dr. Syed Hamad Shirazi is an accomplished academic and researcher in the field of Computer Science, with a specialization in Medical Image Processing, Artificial Intelligence (AI), and Machine Learning. He holds a Ph.D. in Computer Science from Hazara University, where his doctoral work focused on the development of intelligent systems for medical image analysis. Dr. Shirazi began his academic career as a Lecturer in Computer Science with the Higher Education Department in 2008, where he served for a decade and received the Best Teacher Award from the Government of Khyber Pakhtunkhwa. In 2018, he joined Hazara University as an Assistant Professor, where he currently serves as the Graduate Coordinator and BS-AI Program Coordinator in the Department of Computer Science. He has published over 50 research articles, with more than 30 in W category journals, and contributed to two book chapters. His research focuses on the application of deep learning and machine learning techniques to medical diagnosis, including blood cell classification, cervical nuclei segmentation, eczema image analysis, and Meibomian Gland Dysfunction quantification. Notably, he is the Principal Investigator of the NRPU-funded project titled Disease Prediction Support System for Anaemic RBCs, in collaboration with Shaukat Khanum Memorial Cancer Hospital & Research Centre. Currently he is working as PI on a funded project titled" Remote Sensing and Geospatial Analysis for Modeling and Predicting the Impacts of Climate Change on Glacier Water Resources and Crop Mapping in Pakistan” The study proposes a hybrid model that combines Temporal Convolutional Networks (TCNs) with optical flow estimation for accurate crop mapping. 2.34 million Rupees. (In progress). Dr. Shirazi’s collaborative research extends to ciphertext classification, Urdu OCR and speech recognition, and image enhancement for SEM images, with contributions published in Q1 journals such as PLOS ONE, Computers in Biology and Medicine, BMJ Open, Neural Computing, and Neurocomputing. He is also currently supervising 5 Ph.D. and 5 MS scholars, in addition to having successfully supervised 15 MS and 2 Ph.D. students. His future research aims to continue enhancing AI-driven solutions for early disease detection, supporting non-invasive, intelligent diagnostics, and contributing meaningfully to AI literacy and education in both academia and society

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