Imperial College London

DrBennyLo

Faculty of MedicineDepartment of Surgery & Cancer

Senior Lecturer
 
 
 
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Contact

 

+44 (0)20 7594 0806benny.lo Website

 
 
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Location

 

B414BBessemer BuildingSouth Kensington Campus

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Summary

 

Summary

Dr. Benny Lo is a Senior Lecturer of the Hamlyn Centre, and the Department of Surgery and Cancer, Imperial College London. He also serves as an Associate Editor of the IEEE Journal on Biomedical and Health Informatics, and the Chair of IEEE EMBS Wearable Biomedical Sensors and Systems Technical Committee . He is one of the pioneers in Body Sensor Networks (BSN) research, and helped building the foundation of the BSN research through the development of the platform technologies, introduction of novel sensors, approaches and theories for different pervasive applications, and organising conferences and tutorials. 

His current research focuses on pervasive sensing, computer vision, machine learning, Body Sensor Networks (BSN), Internet of Things (IoT) and Wearable Robots and their applications in healthcare, sports and wellbeing.

In collaboration with Coursera, Dr Lo has launched a MOOC specialisation on Advanced App Development on Android covering topics on computer graphics and virtual reality app developments. 

Publications

Journals

Gil B, Anastasova S, Lo B, 2022, Graphene field-effect transistors array for detection of liquid conductivities in the physiological range through novel time-multiplexed impedance measurements, Carbon, Vol:193, ISSN:0008-6223, Pages:394-403

Zhang D, Barbot A, Seichepine F, et al., 2022, Micro-object pose estimation with sim-to-real transfer learning using small dataset, Communications Physics, Vol:5, ISSN:2399-3650

Li Y, Peng C, Zhang Y, et al., 2022, Adversarial learning for semi-supervised pediatric sleep staging with single-EEG channel., Methods

Lam K, Chen J, Wang Z, et al., 2022, Machine learning for technical skill assessment in surgery: a systematic review, Npj Digital Medicine, Vol:5, ISSN:2398-6352

Gu X, Guo Y, Yang G-Z, et al., 2022, Cross-domain self-supervised complete geometric representation learning for real-scanned point cloud based pathological gait analysis, Ieee Journal of Biomedical and Health Informatics, Vol:26, ISSN:2168-2194, Pages:1034-1044

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