About Inam Khan
Dr. Khan is a Postdoctoral Fellow at the O'Donnell Data Science and Research Computing Institute (ODSRCI) at Southern Methodist University, where he leverages SMU's M3 and NVIDIA DGX SuperPOD HPC platforms to advance AI and machine learning research on critical infrastructure challenges. His work spans smart grid analytics, energy systems optimization, AI-driven anomaly detection and forecasting for intelligent mobility systems (electric vehicles, charging infrastructure, and aerial platforms), graph learning for innovation ecosystems, and big-data analytics for urban development. His electricity theft detection framework achieved 98% accuracy and was deployed at the State Grid Corporation of China.
He holds a PhD from Lancaster University's Energy Centre (UK) and has held prior research and faculty positions at Lancaster University, Edge Hill University, and COMSATS University Islamabad. He has authored over 20 publications with 500+ citations, primarily as lead author in flagship IEEE Transactions journals (Smart Grid, Power Systems, Energy Conversion, Instrumentation and Measurements, Engineering Management, and Computational Social Systems). His current interests include data center energy infrastructure, CO₂ emission control, the Energy–Water–Hydrogen nexus, sustainable urban growth modeling, and real-time critical infrastructure monitoring on GPU-accelerated HPC systems.