Imperial College London

Professor Timothy Constandinou

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Professor of Bioelectronics
 
 
 
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Contact

 

+44 (0)20 7594 0790t.constandinou Website

 
 
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Assistant

 

Miss Izabela Wojcicka-Grzesiak +44 (0)20 7594 0701

 
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Location

 

B407Bessemer BuildingSouth Kensington Campus

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Summary

 

Summary

Timothy Constandinou is Professor of Bioelectronics at Imperial College London, Director of the Next Generation Neural Interfaces (NGNI) Lab and Head of the Circuits & Systems (CAS) Research Group. He is also a Group Leader within the UK Dementia Research Institute, Care Research & Technology Centre.

His research interests are in microelectronics, biomedical microsystems, implantable medical devices, neural interfaces, brain-machine interfaces, research platforms, and remote sensing using ultra-wideband radar. 

His lab focuses on creating innovative neurotechnologies to enable communication between the nervous system and electronic devices to study, manage, or treat neurological conditions.

NGNI Lab page: https://www.imperial.ac.uk/next-generation-neural-interfaces

Profiles on: Google Scholar, LinkedIn, Twitter, and Orcid.

Selected Publications

Journal Articles

Ahmadi N, Constandinou TG, Bouganis C-S, 2021, Robust and accurate decoding of hand kinematics from entire spiking activity using deep learning, Journal of Neural Engineering, Vol:18, ISSN:1741-2552, Pages:1-23

Liu Y, Urso A, Martins da Ponte R, et al., 2020, Bidirectional bioelectronic interfaces: system design and circuit implications, Ieee Solid-state Circuits Magazine, Vol:12, ISSN:1943-0582, Pages:30-46

Lauteslager T, Tommer M, Lande TS, et al., 2019, Coherent UWB radar-on-chip for in-body measurement of cardiovascular dynamics, IEEE Transactions on Biomedical Circuits and Systems, Vol:13, ISSN:1932-4545, Pages:814-824

Luan S, Williams I, Maslik M, et al., 2018, Compact standalone platform for neural recording with real-time spike sorting and data logging, Journal of Neural Engineering, Vol:15, ISSN:1741-2552, Pages:1-13

Liu Y, Luan S, Williams I, et al., 2017, A 64-Channel Versatile Neural Recording SoC with Activity Dependant Data Throughput, IEEE Transactions on Biomedical Circuits and Systems, Vol:11, ISSN:1932-4545, Pages:1344-1355

Leene L, Constandinou TG, 2017, Time domain processing techniques using ring oscillator-based filter structures, IEEE Transactions on Circuits and Systems. Part 1: Regular Papers, Vol:64, ISSN:1549-8328, Pages:3003-3012

Conference

Toth R, Zamora M, Ottaway J, et al., 2020, DyNeuMo Mk-2: an investigational circadian-locked neuromodulator with responsive stimulation for applied chronobiology, 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), IEEE, Pages:3433-3440, ISSN:0884-3627

Ahmadi N, Cavuto ML, Feng P, et al., 2019, Towards a distributed, chronically-implantable neural interface, 9th IEEE/EMBS International Conference on Neural Engineering (NER), IEEE, Pages:719-724, ISSN:1948-3546

More Publications