Summary
Lei Kuang is currently a research assistant in the Centre for Bio-Inspired Technology, developing a handheld point-of-care diagnostic system for the rapid detection of infectious diseases. As a member of a highly multidisciplinary team, his work focuses on delivering a comprehensive biomedical device that involves not only the embedded hardware, firmware, and software development, but also the implementation of algorithms specific to sensor calibration and readout, closed-loop control system for temperature regulation, and DNA detection.
At the same time, Lei Kuang is also a Ph.D. student under the supervision of Prof. Pantelis Georgiou and Prof. Martyn Boutelle, conducting research on the next generation of Lab-on-Chip platforms for high-throughput CMOS ISFET arrays. His research aims to introduce a novel framework that leverages compression algorithms and artificial intelligence to boost system efficiency and improve sensor performance. A comprehensive SoC design that monolithically integrates CMOS ISFET arrays and multi-functional processors for edge computation of artificial intelligence serves as the main objective to explore novel biomedical phenomena. His research interests include high-throughput digital readout systems, image compression, machine learning algorithms to improve sensor performance, digital IC design, and real-time processing systems on FPGA for Lab-on-Chip applications.
Prior to his research journey, Lei Kuang received M.Sc. degrees in Embedded Systems, and Analogue & Digital Integrated Circuit Design from the University of Southampton and Imperial College London, both with distinction. During his undergraduate studies at the University of Shanghai for Science and Technology (USST), he obtained his bachelor's degree with first-class honors in industrial electronics and control engineering.
Publications
L. Kuang, J. Zeng and P. Georgiou, "On-Chip Compressed Sensing with CMOS ISFET Arrays for Biomedical Applications," 2023 IEEE Biomedical Circuits and Systems Conference (BioCAS), Toronto, ON, Canada, 2023, pp. 1-5, doi
T. Zhu, L. Kuang, C. Piao, J. Zeng, K. Li and P. Georgiou, "Population-Specific Glucose Prediction in Diabetes Care With Transformer-Based Deep Learning on the Edge," in IEEE Transactions on Biomedical Circuits and Systems, doi
Y. Xu, L. Kuang, T. Zhu, J. Zeng and P. Georgiou, "Drift Prediction and Chemical Reaction Identification for ISFETs using Deep Learning," 2023 IEEE International Symposium on Circuits and Systems (ISCAS), Monterey, CA, USA, 2023, pp. 1-5, doi
T. Zhu, T. Chen, L. Kuang, J. Zeng, K. Li and P. Georgiou, "Edge-Based Temporal Fusion Transformer for Multi-Horizon Blood Glucose Prediction," 2023 IEEE International Symposium on Circuits and Systems (ISCAS), Monterey, CA, USA, 2023, pp. 1-5, doi
J. Zeng, L. Kuang, C. Cicatiello, A. Sinha, N. Moser, M. Boutelle, P. Georgiou, "A LoC Ion Imaging Platform for Spatio-Temporal Characterisation of Ion-Selective Membranes," in IEEE Transactions on Biomedical Circuits and Systems (TBioCAS), 2022, doi
T. Zhu, L. Kuang, J. Daniels, P. Herrero, K. Li and P. Georgiou, "IoMT-Enabled Real-time Blood Glucose Prediction with Deep Learning and Edge Computing," in IEEE Internet of Things Journal (IoT-J), 2022, doi
L. Kuang, T. Zhu, K. Li, J. Daniels, P. Herrero and P. Georgiou, "Live Demonstration: An IoT Wearable Device for Real-time Blood Glucose Prediction with Edge AI," 2021 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2021, pp. 01-01, doi
L. Kuang, J. Zeng and P. Georgiou, "Live Demonstration: Real-Time and High-Speed Ion Imaging Using CMOS ISFET Arrays," 2021 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2021, pp. 01-01, doi
J. Zeng, L. Kuang, M. Cacho-Soblechero and P. Georgiou, "An Ultra-High Frame Rate Ion Imaging Platform Using ISFET Arrays With Real-Time Compression," in IEEE Transactions on Biomedical Circuits and Systems (TBioCAS), vol. 15, no. 4, pp. 820-833, Aug. 2021, doi
T. Zhu, L. Kuang, K. Li, J. Zeng, P. Herrero and P. Georgiou, "Blood Glucose Prediction in Type 1 Diabetes Using Deep Learning on the Edge," 2021 IEEE International Symposium on Circuits and Systems (ISCAS), 2021, pp. 1-5, doi
L. Kuang, J. Zeng and P. Georgiou, "A USB 3.0 High Speed Digital Readout System with Dynamic Frame Rate Processing for ISFET Lab-on-Chip Platforms," 2021 IEEE International Symposium on Circuits and Systems (ISCAS), 2021, pp. 1-5, doi
T. Zhu, K. Li, L. Kuang, P. Herrero, and P. Georgiou, "An Insulin Bolus Advisor for Type 1 Diabetes Using Deep Reinforcement Learning," Sensors, vol. 20, no. 18, p. 5058, 2020, doi
J. Zeng, L. Kuang, N. Miscourides and P. Georgiou, "A 128 × 128 Current-Mode Ultra-High Frame Rate ISFET Array With In-Pixel Calibration for Real-Time Ion Imaging," in IEEE Transactions on Biomedical Circuits and Systems (TBioCAS), vol. 14, no. 2, pp. 359-372, April 2020, doi
L. Kuang, J. Zeng and P. Georgiou, "High-Throughput Digital Readout System for Real-Time Ion Imaging using CMOS ISFET Arrays," 2020 IEEE International Symposium on Circuits and Systems (ISCAS), 2020, pp. 1-5, doi