Imperial College London


Faculty of Natural SciencesDepartment of Chemistry

Professor of Theoretical Chemistry







Molecular Sciences Research HubWhite City Campus





The Yaliraki group is interested in the emergent properties of self-assembling systems in confined environments. Examples from biology include the mechanisms of fibril and viral capsid formations. Another area of interest is the electronic properties of molecular scale junctions. A unifying theme of our work is how geometry and topology affect the dynamics of systems at different scales. Emphasis is on coarse-graining and system reduction approaches.




Hodges M, Yaliraki SN, Barahona M, 2019, Edge-based formulation of elastic network models, Physical Review Research, Pages:033211-033211

Peach R, Yaliraki S, Lefevre D, et al., 2019, Data-driven unsupervised clustering of online learner behaviour , Npj Science of Learning, Vol:4, ISSN:2056-7936

Altuncu MT, Mayer E, Yaliraki SN, et al., 2019, From free text to clusters of content in health records: An unsupervised graph partitioning approach, Applied Network Science, Vol:4, ISSN:2364-8228


Chrysostomou S, Roy R, Prischi F, et al., 2019, Targeting RSK4 prevents both chemoresistance and metastasis in lung cancer, AACR Annual Meeting on Bioinformatics, Convergence Science, and Systems Biology, AMER ASSOC CANCER RESEARCH, ISSN:0008-5472

Prischi F, Chrysostomou S, Roy R, et al., 2019, Targeting RSK4 prevents both chemoresistance and metastasis in lung and bladder cancer, FEBS Open Bio, WILEY, Pages:330-330, ISSN:2211-5463

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