email: klepl@cs.cas.cz
ORCID: 0000-0001-7584-9074
Google Scholar: Dominik Klepl
GitHub: dominikklepl
LinkedIn: dominikklepl
CV: PDF
Postdoctoral researcher at the Complex Networks & Brain Dynamics Group, ICS CAS Prague, building machine learning tools to understand and predict psychiatric disorders from brain imaging data.
Research interests
- Computational psychiatry — primarily schizophrenia
- Self-supervised & semi-supervised learning for neuroimaging
- Normative modeling and brain embedding spaces
- Graph neural networks for multimodal fMRI/EEG
- Schizophrenia subtyping and biomarker discovery
News
- Feb 2026 — New preprint: Domain Adaptation Enables Cross-site Classification of First-episode Schizophrenia from Multimodal Neuroimaging Data
- Jan 2026 — Started MSCA-CZ fellowship: Semi-Supervised Pre-trained Neural Networks for Schizophrenia Subtyping
- Jan–Dec 2025 — Fellowship: Program for supporting promising human resources, Czech Academy of Sciences (PPPLZ L100302451)
- Jan 2025 — Lead researcher on Population-graph approaches for multi-modal modelling of schizophrenia (CAS AV21 program)
Grants & Fellowships
Semi-Supervised Pre-trained Neural Networks for Schizophrenia Subtyping, Lead researcher (active)
Operational Programme Johannes Amos Comenius (MSCA-CZ No. 250507), Ministry of Education, Youth and Sports, Jan 2026 – Dec 2027
Population-graph approaches for multi-modal modelling of schizophrenia, Lead researcher
CAS AV21 “AI” program (AV21-VP34/2025), Czech Academy of Sciences, Jan–Dec 2025
Program for supporting promising human resources, Fellowship
Czech Academy of Sciences (PPPLZ L100302451), Jan–Dec 2025
Predicting functional outcomes in schizophrenia from multimodal neuroimaging and clinical data, Team member
Czech Health Research Council (NU21-08-00432), Feb–Dec 2024