Dr. Muhammad Shahzad

Dr. Muhammad Shahzad is a dedicated and passionate educator in the field of computer science. His research interests include AI in medicine, computational cancer genomics, and explainable AI.

In his academic background, he completed his Ph.D. in Computer Science from FAST - National University of Computer and Emerging Sciences in 2023, focusing on predicting drug response in cancer cell lines using deep learning. His Ph.D. research resulted in three impact factor publications, and he has continued to publish in top-tier journals and conferences. Moreover, he holds double master’s degrees in computer science from Hamdard University and Federal Urdu University of Arts, Science & Technology, and a BS in Computer Science from Shah Abdul Latif University, Khairpur.

As a passionate educator and researcher, Dr. Shahzad is committed to inspiring and educating the next generation of computer scientists and researchers. His dedication to advancing the field through innovative and impactful research has made him a valuable asset to Pakistan.

With 22 years of experience in different institutions such as FAST NUCES, PAK-KIET, Usman Institute of Technology, MAJU, SZABIST, and Baqai Medical University, Dr. Shahzad has taught a range of courses at the graduate and undergraduate levels, including Applied Machine Learning, Data Science Tools and Techniques, Theory of Automata, Bioinformatics, Compiler Construction, and Programming Fundamentals.

Dr. Shahzad's research expertise lies in AI in medicine, computational cancer genomics, and explainable AI. His research has been recognized internationally, with publications in prestigious journals such as the International Journal of Imaging Systems and Technology, Frontiers in Molecular Biosciences, and Diagnostics. He has also supervised research projects on topics including drug response prediction, biological marker identification, and explainable AI.

During his Ph.D. journey, he was a visiting research scholar at InfoLab21, Bailrigg Campus, Lancaster University, UK. He received a grant under the International Research Support Initiative Program (IRSIP) for this research journey. He carried out multiple experiments involving the implementation of a deep learning model to predict drug response in a panel of cancer cell lines.

Dr. Shahzad is persistent, adaptive, and hardworking, with a keen interest in teaching and research areas such as AI in medicine, computational cancer genomics, and explainable AI. Dr. Shahzad is a valuable asset for GU TECH, and it is an honor to welcome him as a faculty member of the computer science department at GU TECH.