Lecturer in Electronics Engineering, School of Computing and Digital Media
Biography
Dr Innocent Lubangakene is a Lecturer in Electronics Engineering and Course Leader for Biomedical Engineering at London Metropolitan University. In his academic role, he teaches and leads modules across electronics, Robotics and biomedical engineering, while contributing to curriculum development, module design, assessment, laboratory teaching, student supervision and academic enhancement. His teaching combines theoretical principles with practical applications in electronics, RF systems, wireless communications, embedded systems and emerging technologies.
His research focuses on non-invasive electromagnetic sensing for biomedical applications, particularly the development of RF and microwave-based technologies for physiological monitoring and healthcare diagnostics. His work integrates RF sensing, antenna and sensor design, electromagnetic characterisation, experimental measurement and data analysis, with a particular interest in applying artificial intelligence and machine learning to interpret sensor data and develop intelligent, data-driven systems for assessing hydration status. His broader research aims to advance accessible, non-invasive and intelligent sensing technologies for continuous and personalised health monitoring.
Through his teaching and research, Dr Lubangakene aims to bridge the gap between electronics engineering and biomedical innovation, developing technologies that can support intelligent, non-invasive and data-driven approaches to healthcare monitoring and diagnostics.
Publications
- Lubangakene, Innocent D., et al. "Effect of Metabolite and Temperature on Artificial Human Sweat Characteristics over a Very Wide Frequency Range (400 MHz–10.4 GHz) for Wireless Hydration Diagnostic Sensors." Results in Engineering, vol. 19, 2023, p. 101328, https://doi.org/10.1016/j.rineng.2023.101328.
- Rajaguru Jayanthi, Renu K., et al. "The Effect of Temperature on Permittivity Measurements of Aqueous Solutions of Glucose for the Development of Non-invasive Glucose Sensors Based on Electromagnetic Waves." Results in Engineering, vol. 20, 2023, p. 101506, https://doi.org/10.1016/j.rineng.2023.101506.
- Hamad, Ahmed R., et al. "Rectenna Design Optimized by Binary Genetic Algorithm for Hybrid Energy Harvesting Applications Across 5G Sub-6 GHz Band." Radio Science, vol. 60, no. 6, 2025, p. e2024RS008154, https://doi.org/10.1029/2024RS008154.
- Al-Gburi, Rasool M., Alibakhshikenari, Mohammad, Virdee, Bal S., Hameed, Teba M., Mariyanayagam, Dion, Fernando, Sandra, Lubangakene, Innocent, Tang, Yi, Khan, Salah Uddin and Elwi, Taha A.. "Microwave-based breast cancer detection using a high-gain Vivaldi antenna and metasurface neural network approach for medical diagnostics" Frequenz, vol. 79, no. 7-8, 2025, pp. 311-325. https://doi.org/10.1515/freq-2024-0190
- Alibakhshikenari, Mohammad, et al. "Design of a Planar Sensor Based on Split-Ring Resonators for Non-Invasive Permittivity Measurement." Sensors, vol. 23, no. 11, 2023, p. 5306, https://doi.org/10.3390/s23115306.
- Riaz, Muhammad, et al. "Sharp Roll-off Triband Microstrip Bandpass Filter with Wide Stopband for Multiband Wireless Communication Systems." International Journal of RF and Microwave Computer-Aided Engineering, vol. 32, no. 12, 2022, p. e23438, https://doi.org/10.1002/mmce.23438.
- Hamad, A. R., Al-Adhami, A., Elmunim, N. A., Alibakhshikenari, M., Virdee, B., Hamad, H. S., et al. (2025). Rectenna design optimized by binary genetic algorithm for hybrid energy harvesting applications across 5G sub-6 GHz band. Radio Science, 60, e2024RS008154. https://doi.org/10.1029/2024RS008154
