Undergraduate Studies - Chemistry (Analytical Chemistry), Saint Petersburg State University 1999-2004
PhD studies - Analytical Chemistry, University of Barcelona 2004 - 2009
Newton International postdoctoral Fellow - Physical Organic and Supramolecular Chemistry, University of Sheffield 2011 - 2013
May 2016 - present - Research Associate in Structural Elucidation of metabolites - Department of Surgery and Cancer, Imperial College London. My main tools for metabolite identification are liquid chromatography (LC) techniques for extraction of unknowns and their characterization by mass spectrometry (MS) and NMR spectroscopy as well as statistical spectroscopic approaches. The source of unknown metabolites are different epidemiological and clinical studies.
January 2013 - May 2016 - Research Associate in Chemistry/Biochemistry working in the project INTERMAP (INTERnational collaborative study of MAcronutrients, micronutrients and blood Pressure) - Imperial College London. Development and application of mass spectrometry methods for phenotyping in large scale epidemiological sample cohorts.
January 2011 - December 2012 - Newton International Fellowship (Royal Society) - Department of Chemistry, University of Sheffield. Project "Cooperativity in Molecular Recognition".
October 2009 - January 2011 - Teaching Assistant (PhD) - Department of Analytical Chemistry, University of Barcelona.
et al., 2022, Metabolome-wide association study on ABCA7 indicates a role of ceramide metabolism in Alzheimer's disease., Proc Natl Acad Sci U S A, Vol:119
et al., 2022, Assessing the clinical value of faecal bile acid profiling to predict recurrence in primary Clostridioides difficile infection, Alimentary Pharmacology and Therapeutics, ISSN:0269-2813
et al., 2022, Diet Patterns Are Associated with Circulating Metabolites and Lipid Profiles of South Asians in the United States, Journal of Nutrition, ISSN:0022-3166
et al., 2022, MS2Query: Reliable and Scalable MS<sup>2</sup> Mass Spectral-based Analogue Search
et al., 2022, Fecal bile acid profiles predict recurrence in patients with primary <i>Clostridioides difficile</i> infection