Andreas Demosthenous

Professor

University College London

United Kingdom

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Professor Andreas Demosthenous is a faculty member at University College London, located in the United Kingdom. His research primarily focuses on the development of microchannel neural interfaces, bioimpedance spectroscopy, and advanced sensor technologies. Recent publications highlight his work on implantable devices for electrical stimulation and recording, as well as innovative solutions for multimodal learning and vehicle suspension systems.

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Collaborators (9)

Nazanin Neshatvar

University College London

UNITED KINGDOM

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Henry Lancashire

University College London

UNITED KINGDOM

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Majid Zamani

University of Southampton

UNITED KINGDOM

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George Malliaras

Prince Philip Professor of Technology

University of Cambridge

UNITED KINGDOM

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Noora Almarri

University College London

UNITED KINGDOM

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Richard Bayford

UNITED KINGDOM

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Dai Jiang

Lecturer

University College London

UNITED KINGDOM

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Erich Sorantin

Medical University of Graz

AUSTRIA

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Jiayang Li

University of Bristol

UNITED KINGDOM

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Andreas Demosthenous

Research Interests

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About

Articles (20)

A 1.76 mW, 355-fps, Electrical Impedance Tomography System With a Simple Time-to-Digital Impedance Readout for Fast Neonatal Lung Imaging

A 30-MHz Wideband 92.7-dB SNR 99.6% Accurate Bioimpedance Spectroscopy IC Using Time-to-Digital Demodulation and Co-Prime Delay-Locked Sampling

Design and Optimization of a High Linearity On-Chip Sinusoidal Current Generator for Bioimpedance Measurements Using Direct Digital Synthesis

An Active Microchannel Neural Interface for Implantable Electrical Stimulation and Recording

Borrowing treasures from neighbors: In-context learning for multimodal learning with missing modalities and data scarcity

Capacitive Sensors for Label-Free Detection in High-Ionic-Strength Bodily Fluids: A Review

A Single‐Stage Differential Amplifier Using Organic Electrochemical Transistors

Performance Improvement in a Vehicle Suspension System with FLQG and LQG Control Methods

Binarized Neural Networks for Resource-Efficient Spike Sorting

Celebrating 75 Years of the IEEE Circuits and Systems Society Across Europe [CASS Conference Highlights]

An 89.3% Current Efficiency, Sub 0.1% THD Current Driver for Electrical Impedance Tomography

High Efficiency Power Management Unit for Implantable Optical-Electrical Stimulators

Efficient Dual Output Regulating Rectifier and Adiabatic Charge Pump for Biomedical Applications Employing Wireless Power Transfer

A Deep Neural Network-Based Spike Sorting With Improved Channel Selection and Artefact Removal

Effects of Patient Recumbency Position on Neonatal Chest EIT

Low Power Analog Processing for Ultra-High-Speed Receivers With RF Correlation

A Fully Implantable Opto-Electro Closed-Loop Neural Interface for Motor Neuron Disease Studies

A Low-Power Recursive I/Q Signal Generator and Current Driver for Bioimpedance Applications

An Implantable Phase Locked Loop MEMS-Based Readout System for Heart Transplantation

A Compact CNN-Based Speech Enhancement With Adaptive Filter Design Using Gabor Function and Region-Aware Convolution

Collaborators (9)

Nazanin Neshatvar

Henry Lancashire

Majid Zamani

George Malliaras

Noora Almarri

Richard Bayford

Dai Jiang

Erich Sorantin

Jiayang Li

Make your next move.