Imperial College London

DrDimitriosAdamos

Faculty of EngineeringDepartment of Computing

Honorary Senior Research Fellow
 
 
 
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Contact

 

d.adamos Website

 
 
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Location

 

304Huxley BuildingSouth Kensington Campus

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Summary

 

Summary

Dr. Dimitrios Adamos is an Honorary Senior Research Fellow for the Department of Computing of Imperial College London and the leader of the #MyBrainTunes experiment held in London’s Science Museum. He is also a co-founder and the CTO of Cogitat, an Imperial College spinout company that develops core AI/ML technology for brain wave decoding.

He holds a MEng in Electrical & Computer Engineering, an MSc in Medical informatics from the School of Medicine and a PhD in Neuroinformatics from the School of Biology of Aristotle University of Thessaloniki, Greece. His research work focuses on machine learning for real-life Brain-Computer Interface applications and has previously featured as invited technology demonstrator for the industry.

Linkedin

Selected Publications

Journal Articles

Barmpas K, Panagakis Y, Bakas S, et al., 2023, Improving generalization of CNN-based motor-imagery EEG decoders via dynamic convolutions, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol:31, ISSN:1534-4320, Pages:1997-2005

Bakas S, Adamos DA, Laskaris N, 2021, On the estimate of music appraisal from surface EEG: a dynamic-network approach based on cross-sensor PAC measurements, Journal of Neural Engineering, Vol:18, ISSN:1741-2560

Georgiadis K, Adamos DA, Nikolopoulos S, et al., 2021, Covariation Informed Graph Slepians for Motor Imagery Decoding, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol:29, ISSN:1534-4320, Pages:340-349

Kosti MV, Georgiadis K, Adamos DA, et al., 2018, Towards an affordable brain computer interface for the assessment of programmers' mental workload, International Journal of Human-Computer Studies, Vol:115, ISSN:1071-5819, Pages:52-66

Adamos DA, Laskaris NA, Micheloyannis S, 2018, Harnessing functional segregation across brain rhythms as a means to detect EEG oscillatory multiplexing during music listening, Journal of Neural Engineering, Vol:15, ISSN:1741-2560

Kalaganis FP, Adamos DA, Laskaris NA, 2018, Musical NeuroPicks: A consumer-grade BCI for on-demand music streaming services, Neurocomputing, Vol:280, ISSN:0925-2312, Pages:65-75

Adamos DA, Dimitriadis SI, Laskaris NA, 2016, Towards the bio-personalization of music recommendation systems: A single-sensor EEG biomarker of subjective music preference, Information Sciences, Vol:343, ISSN:0020-0255, Pages:94-108

Chapters

Laskaris N, Adamos D, Bezerianos A, 2023, Graph Theory for Brain Signal Processing, Handbook of Neuroengineering, Editor(s): Thakor, Springer Nature, ISBN:9789811655401

Conference

Wei X, Faisal AA, Grosse-Wentrup M, et al., 2022, 2021 BEETL competition: advancing transfer learning for subject independence and heterogenous EEG data sets, NeurIPS 2021 Competitions and Demonstrations Track, Proceedings of Machine Learning Research, PMLR, Pages:1-16

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