Dr. Muhammad Irfan Ishaq is an Assistant Professor of Electrical Engineering with over 13 years of experience in teaching, research, and academic administration. He holds a Ph.D. in Electrical Engineering from the National University of Computer and Emerging Sciences (FAST-NUCES), where his doctoral research focused on Predictive Maintenance and Fault Diagnosis of Induction Motors using System Modeling and Deep Learning.

He received his M.Sc. in Electrical Engineering, specializing in Signal Processing and Wave Propagation, from Linnaeus University, Sweden, and his B.E. in Electronic Engineering from NUST-SEECS, Islamabad.

Dr. Irfan has been associated with FAST-NUCES since 2016 and has taught a wide range of courses, including Digital Logic and Design, Computer Organization and Assembly Language, Signals and Systems, Digital Signal Processing, Communications, Control Systems, Linear Circuit Analysis, Electrical Network Analysis, and Electronics.

His academic and administrative experience includes PEC coordination, Outcome-Based Education (OBE), academic accreditation, curriculum development, quality assurance, and program management. He has also served on the Board of Studies, Industrial Advisory Board, and various academic and administrative committees, and has supervised many undergraduate Final Year Projects and graduate research.

His research interests include Machine Learning and Deep Learning, Predictive Maintenance and Fault Diagnosis, Signal Processing, and MIMO/OFDM Communication Systems. His current research focuses on the application of intelligent data-driven techniques for condition monitoring, fault classification, and predictive maintenance of electrical machines.