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Brain-Computer Interfaces, Deep Learning, Machine Learning, Causal Reasoning, Differentiable Signal Processing, Geometric Deep Learning
United Kingdom, Greece

Biography

Currently, I am a Postdoctoral Research Associate at Imperial College London developing Generative Foundation Models for Biosignals used in Brain-Computer Interfaces (BCIs).

ELLIS Member, Fellowship Advance Higher Education and Registered Engineer in Greece (TEE)

PhD Graduate in Computer Science (Artificial Intelligence) from the Department of Computing at Imperial College London, where I conducted my research under the supervision of Professor Stefanos Zafeiriou. My doctoral research, titled “Enhancing Motor-Imagery Brain-Computer Interfaces Through Deep Learning,” explored intersections between Deep Learning and Brain-Computer Interfaces, including Differentiable Signal Processing, Geometric Deep Learning and Causality. I passed my PhD defence with no corrections and my work has been published in top-tier AI venues.

Since 2021, I have been working as a Machine Learning Engineer at Cogitat, where I develop innovative deep learning methods for EEG-based Brain-Computer Interfaces (BCIs). Our groundbreaking technology has been featured by outlets such as the British Computing Society, Sky News, BBC, The Times, The Telegraph, New Statesman and Business Insider. I have also participated in releasing interactive demos showcasing this technology.

In addition to my research, I have actively contributed to the academic community. During my PhD, I served as a PhD Student Academic Representative, co-organized the London Geometry and Machine Learning (LOGML) Summer School, led the Imperial Computing Conference (ICC) and participated in the Equity, Diversity, and Culture Committee at Imperial College London. I have also been involved as a Lakera AI Student Momentum Ambassador and Microsoft Student Ambassador. Furthermore, I have been a reviewer for many prestigious AI journals and conferences.

Prior to my PhD, I completed a Master of Engineering (MEng) at Imperial College London and spent my final year at ETH Zürich, conducting my Master’s thesis under the supervision of Professor Thomas Hofmann.

Activities

Employment (8)

Imperial College London: London, GB

2024-10-01 to present | Postdoctoral Research Associate (Computing)
Employment
Source: Self-asserted source
Konstantinos Barmpas

Cogitat: London, GB

2021-01-01 to present | Machine Learning Engineer
Employment
Source: Self-asserted source
Konstantinos Barmpas

Imperial College London: London, GB

2020-10-01 to 2024-10-01 | PhD Researcher (Computing)
Employment
Source: Self-asserted source
Konstantinos Barmpas

Imperial College London: London, GB

2020-10-01 to 2024-04-01 | Graduate Teaching Assistant (Computing)
Employment
Source: Self-asserted source
Konstantinos Barmpas

Smart Power Networks: London, GB

2020-10-01 to 2021-10-01 | Data Scientist
Employment
Source: Self-asserted source
Konstantinos Barmpas

Facesoft: London, GB

2019-04-01 to 2019-09-01 | Machine Learning / Software Engineering Intern
Employment
Source: Self-asserted source
Konstantinos Barmpas

Udacity: London, GB

2019-03-01 to 2019-09-01 | Student Mentor (Self-Driving Car Engineer Nanodegree)
Employment
Source: Self-asserted source
Konstantinos Barmpas

Imperial College London: London, GB

2019-01-01 to 2019-04-01 | Undergraduate Teaching Assistant (Electrical and Electronic Engineering)
Employment
Source: Self-asserted source
Konstantinos Barmpas

Education and qualifications (3)

Imperial College London: London, GB

2020 to 2024 | PhD (Computing)
Education
Source: Self-asserted source
Konstantinos Barmpas

ETH Zurich: Zurich, CH

2019 to 2020 | Master Year Abroad
Education
Source: Self-asserted source
Konstantinos Barmpas

Imperial College London: London, GB

2016 to 2020 | Master of Engineering (Electrical and Electronic Engineering)
Education
Source: Self-asserted source
Konstantinos Barmpas

Professional activities (5)

ELLIS - European Laboratory for Learning and Intelligent Systems: London, GB

2024-12-01 to present | ELLIS Member
Membership
Source: Self-asserted source
Konstantinos Barmpas

Advance Higher Education: London, GB

2024-11-01 to present | Fellowship
Membership
Source: Self-asserted source
Konstantinos Barmpas

Imperial College London: London, GB

2020-10-01 | Doctoral Scholarship Award (Computing)
Distinction
Source: Self-asserted source
Konstantinos Barmpas

ETH Zurich: Zurich, CH

2019-09-01 | Swiss Mobility Programme Scholarship (Information Technology and Electrical Engineering )
Distinction
Source: Self-asserted source
Konstantinos Barmpas

Imperial College London: London, GB

2018-06-01 | Year Group Project Award (Electrical and Electronic Engineering)
Distinction
Source: Self-asserted source
Konstantinos Barmpas

Works (11)

A Causal Perspective in Brainwave Foundation Models

Causality and Large Models @NeurIPS 2024
2024 | Conference paper
URI:

https://openreview.net/forum?id=IGSDECEKt8

Contributors: Konstantinos Barmpas; Yannis Panagakis; Dimitrios Adamos; Nikolaos Laskaris; Stefanos Zafeiriou
Source: Self-asserted source
Konstantinos Barmpas

Position: Addressing Ethical Challenges and Safety Risks in GenAI-Powered Brain-Computer Interfaces

GenAI for Health: Potential, Trust and Policy Compliance
2024 | Conference paper
URI:

https://openreview.net/forum?id=N8CIlpniXs

Contributors: Konstantinos Barmpas; Georgios Zoumpourlis; Yannis Panagakis; Dimitrios Adamos; Nikolaos Laskaris; Stefanos Zafeiriou
Source: Self-asserted source
Konstantinos Barmpas

A causal perspective on brainwave modeling for brain–computer interfaces

Journal of Neural Engineering
2024-06-01 | Journal article
Contributors: Konstantinos Barmpas; Yannis Panagakis; Georgios Zoumpourlis; Dimitrios A Adamos; Nikolaos Laskaris; Stefanos Zafeiriou
Source: check_circle
Crossref

Subject Selection Framework to Improve Personalised Models for Motor-Imagery BCIs via Wavelets and Graph Diffusion

ICLR 2024 Workshop on Learning from Time Series For Health
2024-03-05 | Conference paper
URI:

https://openreview.net/forum?id=BQjdAAA7Ob

Contributors: Konstantinos Barmpas; Yannis Panagakis; Dimitrios Adamos; Nikolaos Laskaris; Stefanos Zafeiriou
Source: Self-asserted source
Konstantinos Barmpas

BrainWave-Scattering Net: a lightweight network for EEG-based motor imagery recognition

Journal of Neural Engineering
2023-10-01 | Journal article
Contributors: Konstantinos Barmpas; Yannis Panagakis; Dimitrios A Adamos; Nikolaos Laskaris; Stefanos Zafeiriou
Source: check_circle
Crossref

Improving Generalization of CNN-based Motor-Imagery EEG Decoders via Dynamic Convolutions

IEEE Transactions on Neural Systems and Rehabilitation Engineering
2023-04-06 | Journal article
Part of ISSN: 1534-4320
Part of ISSN: 1558-0210
Contributors: Konstantinos Barmpas; Ioannis Panagakis; Stylianos Bakas; Dimitrios A. Adamos; Nikolaos Laskaris; Stefanos Zafeiriou
Source: Self-asserted source
Konstantinos Barmpas
grade
Preferred source (of 2)‎

Surfing on the Neural Sheaf

NeurIPS 2022 Workshop on Symmetry and Geometry in Neural Representations
2022-10-21 | Conference paper
Contributors: Konstantinos Barmpas; Julian Suk; Lorenzo Giusti; Tamir Hemo; Miguel Lopez; Cristian Bodnar
Source: Self-asserted source
Konstantinos Barmpas

A CAUSAL VIEWPOINT ON MOTOR-IMAGERY BRAINWAVE DECODING

ICLR2022 Workshop on the Elements of Reasoning: Objects, Structure and Causality
2022-04-29 | Conference paper
URI:

https://openreview.net/pdf?id=HRfDSrOLclq

Contributors: Konstantinos Barmpas; Yannis Panagakis; Dimitrios Adamos; Nikolaos Laskaris; Stefanos Zafeiriou
Source: Self-asserted source
Konstantinos Barmpas

2021 BEETL Competition: Advancing Transfer Learning for Subject Independence and Heterogenous EEG Data Sets

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track
2022-03-01 | Conference paper
URI:

https://proceedings.mlr.press/v176/wei22a.html

Contributors: Wei, Xiaoxi; Faisal, A. Aldo; Grosse-Wentrup, Moritz; Gramfort, Alexandre; Chevallier, Sylvain; Jayaram, Vinay; Jeunet, Camille; Bakas, Stylianos; Ludwig, Siegfried; Barmpas, Konstantinos et al.
Source: Self-asserted source
Konstantinos Barmpas

Team Cogitat at NeurIPS 2021: Benchmarks for EEG Transfer Learning Competition

NeurIPS 2021 BEETL Competition: Benchmarks for EEG Transfer Learning
2022-02-01 | Preprint
Contributors: Konstantinos Barmpas; Stylianos Bakas; Siegfried Ludwig; Konstantinos Barmpas; Mehdi Bahri; Yannis Panagakis; Nikolaos Laskaris; Dimitrios A. Adamos; Stefanos Zafeiriou
Source: Self-asserted source
Konstantinos Barmpas

Certifying Properties of Deep Networks by Taking them into Shallow Waters

ETH Zurich
2020 | Journal article
Source: Self-asserted source
Konstantinos Barmpas

Peer review (5 reviews for 3 publications/grants)

Review activity for IEEE journal of biomedical and health informatics. (1)
Review activity for IEEE transactions on pattern analysis and machine intelligence. (2)
Review activity for Patterns. (2)