About
Dr. Umar Saleem
Dr. Umar Saleem is a postdoctoral researcher specializing in prognostics and health management (PHM) of aircraft
electrical systems and advanced energy technologies. He earned his Ph.D. in Electrical Engineering from Northwestern
Polytechnical University, China, where he developed AI-driven models for state of health (SOH) estimation and remaining
useful life (RUL) prediction of batteries, IGBTs, and aero-engines. His work integrates deep learning, system modeling,
and experimental validation to enhance the safety and reliability of aerospace and energy storage systems. He has
published first-author Q1 journal articles in Electrochimica Acta, Energies, and
Computers & Electrical Engineering, and presented at major IEEE conferences. With prior industry experience
in substations, smart grids, and renewable integration, he bridges academic innovation with practical engineering
applications and is passionate about collaboration, mentorship, and advancing AI-powered solutions for sustainable energy
and aerospace systems.
Qualifications
Academic Degrees
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Ph.D. in Electrical Engineering, Northwestern Polytechnical University, Xi’an, China (2019–2025)
Dissertation: Prognostics and Health Management of Aircraft Electric Systems
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MS in Electrical (Power) Engineering, The Superior College, Lahore, Pakistan (2015–2018)
Thesis: Fault Detection and Diagnosis of Transmission Lines using Wavelet Transform
- B.Tech (Electrical, Hons), The Islamia University of Bahawalpur, Pakistan (2012–2015)
- Diploma of Associate Engineering (Electrical Technology), PBTE Lahore, Pakistan (2009–2012)
Professional Certifications
- Electrical Supervisor License — Government of Pakistan
- AutoCAD (Electrical) Certification
- Training in High-Voltage Testing, Substation Protection, and Relay Coordination
Professional Memberships
- IEEE Member (Membership #93636993)
- Energy Institute UK — Graduate Member (Member #0085345)
- National Technology Council (Pakistan) — Registered Professional Engineering Technologist
Appointments
Research focus: PHM of aircraft electrical systems, battery SOH/RUL prediction, and reliability of wide-bandgap devices (SiC, GaN).
AI-driven PHM of aircraft power system components including batteries, IGBTs, and aero-engines.
Commissioning, testing, and troubleshooting of 220/132 kV substations; relay programming and fault analysis.
Delivered undergraduate courses in power systems, electrical machines, and protection.
Designed and maintained HT/LT panels; supervised three-phase motor systems.