About Dr Umair Shahzad
I'm a Lecturer in Engineering. I completed my PhD in Electrical Engineering from the University of Nebraska-Lincoln (USA). I completed my MSc in Electrical Engineering and BSc in Electrical Engineering from the University of Nottingham (UK) and the University of Engineering and Technology, Lahore (Pakistan), respectively.
My PhD research focused on risk-based machine learning approaches for power system probabilistic transient stability. The associated findings have been widely published and cited in numerous high-impact factor journals and top conferences.
Prior to commencing my role at the University of Sunderland in 2023, I had three years of teaching experience at different universities in Pakistan. During this period, I taught a wide range of modules including Electrical Network Analysis, Power Generation and Utilisation, Industrial Process Control, Electric Circuit Analysis, Control Systems, DC Machines, and Measurements and Instrumentation.
Teaching and supervision
Courses:
Modules:
- Electronic and Electrical Principles (EAT119)
- Computer Aided Engineering (EAT216)
- Mathematics, Statistics and Simulation (EAT239)
- Electrical Power (ELX303)
- Instrumentation and Data Analysis (EDA105)
- Industrial Electronic Systems (EDA305).
Supervision:
- Engineering Interdisciplinary Project (EAT246)
- Project (ENX313)
- Project/Dissertation (ENGM123)
- Professional Practice (ENGM124).
Research
- Electrical Power Systems
- Grid Integration of Renewable Generation
- Power System Probabilistic Stability
- Power System Risk Assessment
- Machine Learning for Power Systems
- PhD Dissertation(opens in new tab)
- Google Scholar(opens in new tab)
- ResearchGate(opens in new tab).
Further information
- Lifetime Member of Pakistan Engineering Council (PEC)
- Recipient of Fulbright Scholarship (University of Nebraska-Lincoln, USA)
- Recipient of Developing Solutions Scholarship (University of Nottingham, UK)
- Recipient of Best Lecturer Award (University of Faisalabad, Pakistan)
- LinkedIn(opens in new tab)
- Google Scholar(opens in new tab)
- ResearchGate(opens in new tab)
- ORCID(opens in new tab).
