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Dr Umair Shahzad


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Lecturer in Engineering

I am a Lecturer in the School of Computer Science and Engineering. I completed my PhD in Electrical Engineering from University of Nebraska-Lincoln (USA). I completed my MSc in Electrical Engineering and BSc in Electrical Engineering from University of Nottingham (UK) and 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 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:

  • BEng (Hons) Electronic and Electrical Engineering
  • BEng (Hons) Mechanical Engineering
  • BEng Electronic and Electrical Engineering Practice


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 interests for potential research students

My research focus includes but is not limited to electrical power systems, power system probabilistic stability, power system risk assessment, and machine learning for power systems. I am open to collaboration and interested collaborators/students may contact me at my email address.

Research

  • Electrical Power Systems
  • Grid Integration of Renewable Generation 
  • Power System Probabilistic Stability
  • Power System Risk Assessment
  • Machine Learning for Power Systems

  • Electrical Engineering
  • Electrical Power Systems
  • Power System Probabilistic Stability
  • Power System Risk Assessment
  • Machine Learning for Power Systems

    • 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
  • Google Scholar
  • ResearchGate
  • ORCID

Last updated 10 December 2024