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Dr. Tomás Codina

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Technische Universität Berlin
Intelligent Biomedical Sensing (IBS)

Marchstraße 23, 10587 Berlin
https://ibs-lab.com/people/

Dr. Tomás Codina

Postdoctoral Researcher

Affiliation:  BIFOLD

Tomas Codina is a Postdoctoral Researcher at the Intelligent Biomedical Sensing Lab at Technische Universität Berlin, where he works on multimodal neuroimaging with a focus on fNIRS–EEG fusion in naturalistic environments. His research centers on machine- and deep-learning approaches for multimodal neuroimaging, with a particular focus on developing unsupervised, data-driven methods that integrate fNIRS/DOT, EEG, and physiological or environmental signals. He is also actively involved in the data acquisition and analysis components of multimodal fNIRS–EEG pipelines. His interests include enabling continuous brain imaging in real-world conditions and exploring how these multimodal frameworks can be translated toward clinical applications.

 

He completed his PhD in theoretical high-energy physics at Humboldt University of Berlin under the supervision of Prof. Dr. Olaf Hohm, graduating *summa cum laude*. From 2020 to 2023, his doctoral research focused on higher-derivative corrections in string theory, particularly for cosmological and black-hole backgrounds. He previously earned his *Licenciatura* in Physics—equivalent to a combined bachelor’s and master’s degree—at the University of Buenos Aires in Argentina.

Neurotechnology, Neuroimaging, Multimodal fusion, fNIRS, EEG.

E. Middell, L. Carlton, S. Moradi, T. Codina, T. Fischer, J. Cutler, S. Kelley, J. Behrendt, T. Dissanayake, N. Harmening, M. A. Yücel, D. A. Boas, A. von Lühmann

Cedalion Tutorial: A Python-based framework for comprehensive analysis of multimodal fNIRS & DOT from the lab to the everyday world

January 09, 2026
https://doi.org/10.48550/arXiv.2601.05923

News
BIFOLD Update| Sep 18, 2025

IBS Lab Contribution to fNIRS UK 2025

At fNIRS UK 2025 in Cambridge, IBS Lab will showcase ERC-funded research on multimodal neuroimaging, including a Cedalion toolbox workshop, advances in fNIRS-EEG fusion, and deep learning transfer from fMRI to fNIRS/DOT.