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Tamás Karácsony. Completed the Master in Mechatronical Engineering in 2020/01/20 by Budapesti Muszaki és Gazdaságtudományi Egyetem Gépészmérnöki Kar, Master in Biomedical Engineering in 2018/08/10 by Danmarks Tekniske Universitet and Bachelor in Mechatronical Engineer in 2016/01/20 by Budapesti Muszaki és Gazdaságtudományi Egyetem Gépészmérnöki Kar. Attends the Doutoramento in Engenharia Electrotécnica e de Computadores by Universidade do Porto Faculdade de Engenharia since 2021/10/18. Is Researcher in Instituto de Engenharia de Sistemas e Computadores Tecnologia e Ciência. In his curriculum Ciência Vitae the most frequent terms in the context of scientific, technological and artistic-cultural output are: Computer Vision; Deep learning; Action recognition; Epileptic seizure semiology; Diagnostic support; Computer Vision and Pattern Recognition (cs; CV); FOS: Computer and information sciences; I; 4; 8; 2; 10; 0; .
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Identification

Personal identification

Full name
Tamás Karácsony

Citation names

  • Karácsony, Tamás

Author identifiers

Ciência ID
2D1F-A324-CFE0
ORCID iD
0000-0002-7899-1786
Google Scholar ID
14aXjRgAAAAJ
Scopus Author Id
57207828053

Email addresses

  • tamas.karacsony@inesctec.pt (Professional)

Languages

Language Speaking Reading Writing Listening Peer-review
Hungarian (Mother tongue)
English Advanced (C1) Advanced (C1) Advanced (C1) Advanced (C1) Advanced (C1)
German Elementary (A2) Elementary (A2) Elementary (A2) Elementary (A2) Elementary (A2)
Education
Degree Classification
2021/10/18 - 2025/08/31
Ongoing
 Engenharia Electrotécnica e de Computadores (Doutoramento)
Universidade do Porto Faculdade de Engenharia, Portugal
"Explainable Deep Learning Based Epileptic Seizure Classification with Clinical 3D Motion Capture" (THESIS/DISSERTATION)
2016/02/01 - 2020/01/20
Concluded
 Mechatronical Engineering (Master)
Major in Mechatronical Engineering
Budapesti Muszaki és Gazdaságtudományi Egyetem Gépészmérnöki Kar, Hungary
"Motion-based Epileptic Seizure Classification with Deep Learning" (THESIS/DISSERTATION)
 Excellent with highest honours
2016/09/01 - 2018/08/10
Concluded
 Biomedical Engineering (Master)
Major in Biomedical Engineering
Danmarks Tekniske Universitet, Denmark
"Hybrid Motor Imagery Brain Computer Interface and Virtual Reality based system for neurorehabilitation of stroke patients, employing deep learning classification" (THESIS/DISSERTATION)
 Excellent with honours
2012/09/01 - 2016/01/20
Concluded
 Mechatronical Engineer (Bachelor)
Major in Mechatronical Engineer
Budapesti Muszaki és Gazdaságtudományi Egyetem Gépészmérnöki Kar, Hungary
"Analysis of amputated limb and prosthesis socket connection using the finite element method" (THESIS/DISSERTATION)
 Excellent
Affiliation

Science

Category
Host institution 		Employer
2021/10/11 - Current Research Assistant (Research) Universidade do Porto Faculdade de Engenharia, Portugal
Universidade do Porto Faculdade de Engenharia, Portugal
2019/09/04 - Current Researcher (Research) Instituto de Engenharia de Sistemas e Computadores Tecnologia e Ciência, Portugal
Universidade do Porto Faculdade de Engenharia, Portugal
2023/03/01 - 2024/02/29 Visiting Researcher (Research) Carnegie Mellon University, United States
Carnegie Mellon University, United States
Outputs

Publications

Conference paper
  1. Carmona, J; Karacsony, T; Cunha, JPS; Tamás Karácsony; João Carmona; João Paulo Silva Cunha. "BlanketGen - A Synthetic Blanket Occlusion Augmentation Pipeline for Motion Capture Datasets". 2023.
    10.1109/enbeng58165.2023.10175320
  2. Carmona, J; Karacsony, T; Cunha, JPS. "BlanketSet - A Clinical Real-World In-Bed Action Recognition and Qualitative Semi-Synchronised Motion Capture Dataset". 2023.
    10.1109/enbeng58165.2023.10175335
  3. Karacsony, Tamas; Loesch-Biffar, Anna Mira; Vollmar, Christian; Noachtar, Soheyl; Cunha, Joao Paulo Silva. "DeepEpil: Towards an Epileptologist-Friendly AI Enabled Seizure Classification Cloud System based on Deep Learning Analysis of 3D videos". Paper presented in 2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI), 2021.
    Published • 10.1109/bhi50953.2021.9508555
  4. Karacsony, Tamas; Loesch-Biffar, Anna Mira; Vollmar, Christian; Noachtar, Soheyl; Cunha, Joao Paulo Silva. "A Deep Learning Architecture for Epileptic Seizure Classification Based on Object and Action Recognition". Paper presented in ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, 2020.
    Published • 10.1109/icassp40776.2020.9054649
  5. Karácsony, Tamás; Hansen, John Paulin; Iversen, Helle Klingenberg; Puthusserypady, Sadasivan. "Brain Computer Interface for Neuro-rehabilitation With Deep Learning Classification and Virtual Reality Feedback". Paper presented in 10th Augmented Human International Conference 2019 (AH2019), Reims, 2019.
    Published • 10.1145/3311823.3311864
Journal article
  1. Karácsony, Tamás; Loesch-Biffar, Anna Mira; Vollmar, Christian; Rémi, Jan; Noachtar, Soheyl; Cunha, João Paulo Silva. "Novel 3D video action recognition deep learning approach for near real time epileptic seizure classification". Scientific Reports 12 1 (2022): http://dx.doi.org/10.1038/s41598-022-23133-9.
    Open access • Published • 10.1038/s41598-022-23133-9