Dr Lijuan Wang

Lijuan Wang received her BEng degree in Computer Science and Technology from Qiqihar University, Heilongjiang, China in 2010 and her PhD degree in Measurement and Automation from North China Electric Power University (NCEPU), Beijing, China in 2014. She subsequently obtained a second PhD degree in Electronic Engineering from the University of Kent, Canterbury, UK in 2017. After that she worked at the University of Teesside as a Lecturer in Instrumentation and Control Engineering. Since June 2018 she has been a Lecturer in Electronic Engineering at the University of Kent.
She was awarded the Best Student Poster in 2014 I2MTC (International Instrumentation and Measurement Technology Conference), the Best Presentation Award in 2015 ISMTMF (International Symposium on Measurement Techniques for Multiphase Flows), the Prize for Excellent PhD Thesis by NCEPU, the 2015 IEEE Graduate Fellowship by the IEEE Instrumentation and Measurement Society and the 2019 J. Barry Oakes Advancement Award in recognition of her contributions to the development of soft computing models for multiphase flow measurement.
Her main areas of expertise include multiphase flow measurement, condition monitoring of mechanical systems, computational modelling (FEM, CFD), electrostatic sensing, hyperspectral imaging and machine learning. 

• Flow measurement and instrumentation
• Condition monitoring of mechanical systems
• UAV-based remote sensing
• Quality assessment of recycled materials
• Medical image processing

Current Teaching Commitments

• EL025 Engineering Principles (practical sessions)
• EL311 First Year Engineering Applications Project (project supervision)
• EL315 Digital Technologies (sequential logic)
• EL560 Microcomputer Engineering (microcontroller engineering)
• EL562 Engineering Group Project (computer interfacing and project supervision)
• EL673 Digital Systems Design (formal testability)
• EL600 Final Year Project (project supervision)

Previous Teaching Commitments

• Fundamentals of Mathematics
• Introduction to Electronics

PhD research topics

• Condition Monitoring of Wind Turbines through Multispectral Imaging
• Vibration Measurement of Rotor-bearing Systems Using Electrostatic Sensors
• Gas-solid Flow Measurement in Fluidized Beds through Multi-modal Sensing and Deep Learning
• Molten Salt Metering in Solar Power Stations through Multi-modal Sensing and Data Modelling
• CO2 Flow Metering under CCS Conditions Using Coriolis Mass Flowmeters and Soft Computing Techniques

Professional Qualifications

• Member of IEEE
• Fellow of Higher Education Academy

Prizes and Awards

• 2019 J. Barry Oaks Advancement Award “For contribution to the development of soft computing models for multiphase flow measurement”, IEEE Instrumentation and Measurement Society
• 2015 IEEE Graduate Fellowship Award, IEEE Instrumentation and Measurement Society.
• 2015 Excellent PhD Thesis, North China Electric Power University
• 2015 Best Presentation Award, International Symposium on Measurement Techniques For Multiphase Flows, Sapporo, Japan.
• 2014 Best Student Poster Award (1st Place), IEEE International Instrumentation and Measurement Technology Conference, Montevideo, Uruguay.
• 2014 Student Travel Award, IEEE International Instrumentation and Measurement Technology Conference, Montevideo, Uruguay.