Soldatov Aleksandr Vladimirovich

+7(863) 218-40-00 ext. 11077; +7(8634) 68-08-90 ext. 11077;

Звание: Профессор

Degree: Доктор физико-математических наук

Southern Federal University - Scientific supervisor of the research field

Southern Federal University - Chairman

E-mail:

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Personal page:

https://sfedu.ru/s7/person/ru/soldatov

Personal page in english:

https://sfedu.ru/s7/person/en/soldatov

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Research interests:

Nanoscale local atomic, electronic and magnetic structures of advanced smart  materials for nano-, bio-, medical applications.

Synchrotron radiation spectroscopies and x-ray free electron laser experiments.

Multiscale supercomputer modelling in materials science and nanotechnology.

Nano-oncology : Development of optimized synthesis techniques of metal-containing nanoparticles having a pronounced effect on tumor tissue, and integrated technologies for enhancing antitumor resistance mechanisms using nanomaterials and personalized low-intensity systemic effects.

Deep machine learning algorithms (Artificial Intelligence) for the analysis of Big Data, obtained at large-scale research facilities.

Deep machine learning algorithms (Artificial Intelligence) for oncology diagnostics. 

Research projects:

Smart nanostructured porous materials computer nanodesign, advanced chemical synthesis and spectral nanodiagnostics.

From NanoDesign upto NanoDiagnostics of smart nanomaterials:“full cycle” laboratory setup.

Colloidal magnetic nanoparticles for personalized theranostics in oncology: advanced in-situ x-ray spectroscopic and x-ray nano-imaging research.

Picometer scalecharacterization of 3D local atomic structure parameters  of nanomaterials based on XANES spectroscopy.

Nano-oncology : Development of optimized synthesis techniques of metal-containing nanoparticles having a pronounced effect on tumor tissue, and integrated technologies for enhancing antitumor resistance mechanisms using nanomaterials and personalized low-intensity systemic effects.

Deep machine learning algorithms (Artificial Intelligence) for the analysis of Big Data, obtained at large-scale research facilities.

Deep machine learning algorithms (Artificial Intelligence) for oncology diagnostics.