Andon Tchechmedjiev

Andon Tchechmedjiev is Associate Professor at Institut Mines Telecom in the EuroMov Digital Health in Motion (EDHM) interdisciplinary lab (IMT Mines Alès, University of Montpellier), at the crossroads of artificial intelligence, human movement science and embodiment as well as medicine. He is co-PI of the Semantics and Taxonomy of Human Movement research axis and member of the lab steering committee. He also co-animates the data ecosystem and governance theme in the Data & AI scientific community at Institut Mines Telecom. He has co-authored more than 30 peer-reviewed publications in domains as diverse as computational linguistics, knowledge engineering, applied machine learning, medical informatics, computational neuroscience, and computer vision. He is a member of the core group of COST Action NexusLinguarum (computational linguistics) and a participant in COST Action PhysAgNet (human movement, medicine, silver age). He supervises multiple Ph.D. students on motion to language transcription, on functional markers of movement in neuroimaging for post-stroke rehabilitation, and on a cross-cultural studies of movement and embodied process synchronisation. **Semantics and Taxonomy of Movement axis**  https://dhm.euromov.eu/semtaxm/ SemTaxM aims at identifying taxonomic classifications of movement and to defining a theory of the semantics carried by movement and models of semantics grounded in specific contexts. SemTaxM jointly exploits knowledge representation techniques and formalisms from the semantic web with unsupervised multimodal representation learning techniques. The former will help us design ontologies and knowledge bases pertaining to movement taxonomy, semantics (reasoning, semantic summarization) and parametric representations, while the latter will allow us to build underlying mathematical representations that capture multiscale invariants of movement, its complexity and latent properties by fusing and decomposing multimodal observations of movement: parametric models, taxonomic classification, brain activity acquired through non-invasive methods (EEG, NIRS) that exhibit neural signatures of movement and consciousness.