Imperial College London

Professor Pantelis Georgiou

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Professor of Biomedical Electronics



+44 (0)20 7594 6326pantelis Website




902Electrical EngineeringSouth Kensington Campus





Pantelis Georgiou currently holds the position of Professor at Imperial College London within the Department of Electrical and Electronic Engineering. He is the head of the Bio-inspired Metabolic Technology Laboratory in the Centre for Bio-Inspired Technology; a multi-disciplinary group that invents, develops and demonstrates advanced micro-devices to meet global challenges in biomedical science and healthcare.

His research includes ultra-low power micro-electronics, bio-inspired circuits and systems, lab-on-chip technology and application of micro-electronic technology to create novel medical devices. Application areas of his research include new technologies for treatment of diabetes such as the artificial pancreas, novel Lab-on-Chip technology for genomics and diagnostics targeted towards infectious disease and antimicrobial resistance (AMR), and wearable technologies for rehabilitation of chronic conditions.

Prof. Georgiou graduated with a 1st Class Honours MEng Degree in Electrical and Electronic Engineering in 2004 and Ph.D. degree in 2008 both from Imperial College London. He then joined the Institute of Biomedical Engineering as Research Associate until 2010, when he was appointed Head of the Bio-inspired Metabolic Technology Laboratory. In 2011, he joined the Department of Electrical & Electronic Engineering, where he currently holds an academic faculty position. He has made significant contributions to Diabetes technology and has developed the first bio-inspired artificial pancreas for treatment of Type I diabetes using the silicon-beta cell. He has also made significant contributions to the development of integrated chemical-sensing systems in CMOS for Lab-on-Chip applications. He has pioneered the development of the Ion-Sensitive Field Effect Transistor, an integrated pH sensor which is currently being used in next generation DNA sequencing machines and rapid diagnostic systems for detection of infectious diseases.

Prof. Georgiou is a senior member of the IEEE and IET and serves on the BioCAS and Sensory Systems technical committees of the IEEE CAS Society. He is an associate editor of the IEEE Sensors and TBioCAS journals. He is also on the IEEE sensors council. In 2013 he was awarded the IET Mike Sergeant Achievement Medal for his outstanding contributions to engineering and development of the bio-inspired artificial pancreas. In 2017, he was also awarded the IEEE Sensors Council Technical Achievement award. He was also an IEEE Distinguished Lecturer in Circuits and Systems.

Featured Videos

Dr Pantelis Georgiou – “Inventing Solutions to Major Healthcare Challenges”

Microchip Technology enabling rapid diagnostics: from AMR to COVID-19

Imperial Lockdown Lessons: Creating a Hand Held Test for COVID -19

Imperial Global Science Policy Forum - The COVID-19 Response

Recent News

Imperial academics share latest COVID-19 research with international community

COVID-19 Response Fund: Cutting-edge technologies advance coronavirus fight

High-impact COVID-19 projects strengthened by Community Jameel fund

Global collaboration needed to solve coronavirus challenges

Med Tech news: A handheld diagnostic platform for COVID-19 molecular testing

Lab-on-a-Chip (LoC) COVID-19 Test Advances to Clinical Trials

Emerging tech solutions to global AMR threat take centre stage at White City

Imperial team awarded 2018 Rosetrees Trust Interdisciplinary Award

For more news please follow my twitter@pgeorgiou_ic

My Research Team

group photo

Current Research Opportunities

Closing Date Title/ Link to futher information
No Closing Date  PhD in Microelectronics/Bio-Inspired Technology/Medical Devices - Contact me



Zhu T, Li K, Herrero P, et al., 2023, GluGAN: Generating Personalized Glucose Time Series Using Generative Adversarial Networks., Ieee J Biomed Health Inform, Vol:PP

Noaro G, Zhu T, Cappon G, et al., 2023, A Personalized and Adaptive Insulin Bolus Calculator Based on Double Deep Q- Learning to Improve Type 1 Diabetes Management., Ieee J Biomed Health Inform, Vol:27, Pages:2536-2544

Unsworth R, Armiger R, Jugnee N, et al., 2023, Safety and efficacy of an adaptive bolus calculator for Type 1 diabetes: a randomised control cross over study, Diabetes Technology and Therapeutics, ISSN:1520-9156

Mao Y, Miglietta L, Kreitmann L, et al., 2023, Deep domain adaptation enhances Amplification Curve Analysis for single-channel multiplexing in real-time PCR, Ieee Journal of Biomedical and Health Informatics, ISSN:2168-2208

Zhu T, Kuang L, Daniels J, et al., 2023, IoMT-Enabled Real-Time Blood Glucose Prediction With Deep Learning and Edge Computing, Ieee Internet of Things Journal, Vol:10, ISSN:2327-4662, Pages:3706-3719

More Publications